experiment definition environmental science

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Experiment Definition in Science – What Is a Science Experiment?

In science, an experiment is simply a test of a hypothesis in the scientific method . It is a controlled examination of cause and effect. Here is a look at what a science experiment is (and is not), the key factors in an experiment, examples, and types of experiments.

Experiment Definition in Science

By definition, an experiment is a procedure that tests a hypothesis. A hypothesis, in turn, is a prediction of cause and effect or the predicted outcome of changing one factor of a situation. Both the hypothesis and experiment are components of the scientific method. The steps of the scientific method are:

• Make observations.
• Ask a question or identify a problem.
• State a hypothesis.
• Perform an experiment that tests the hypothesis.
• Based on the results of the experiment, either accept or reject the hypothesis.
• Draw conclusions and report the outcome of the experiment.

Key Parts of an Experiment

The two key parts of an experiment are the independent and dependent variables. The independent variable is the one factor that you control or change in an experiment. The dependent variable is the factor that you measure that responds to the independent variable. An experiment often includes other types of variables , but at its heart, it’s all about the relationship between the independent and dependent variable.

Examples of Experiments

Fertilizer and plant size.

For example, you think a certain fertilizer helps plants grow better. You’ve watched your plants grow and they seem to do better when they have the fertilizer compared to when they don’t. But, observations are only the beginning of science. So, you state a hypothesis: Adding fertilizer increases plant size. Note, you could have stated the hypothesis in different ways. Maybe you think the fertilizer increases plant mass or fruit production, for example. However you state the hypothesis, it includes both the independent and dependent variables. In this case, the independent variable is the presence or absence of fertilizer. The dependent variable is the response to the independent variable, which is the size of the plants.

Now that you have a hypothesis, the next step is designing an experiment that tests it. Experimental design is very important because the way you conduct an experiment influences its outcome. For example, if you use too small of an amount of fertilizer you may see no effect from the treatment. Or, if you dump an entire container of fertilizer on a plant you could kill it! So, recording the steps of the experiment help you judge the outcome of the experiment and aid others who come after you and examine your work. Other factors that might influence your results might include the species of plant and duration of the treatment. Record any conditions that might affect the outcome. Ideally, you want the only difference between your two groups of plants to be whether or not they receive fertilizer. Then, measure the height of the plants and see if there is a difference between the two groups.

Salt and Cookies

You don’t need a lab for an experiment. For example, consider a baking experiment. Let’s say you like the flavor of salt in your cookies, but you’re pretty sure the batch you made using extra salt fell a bit flat. If you double the amount of salt in a recipe, will it affect their size? Here, the independent variable is the amount of salt in the recipe and the dependent variable is cookie size.

Test this hypothesis with an experiment. Bake cookies using the normal recipe (your control group ) and bake some using twice the salt (the experimental group). Make sure it’s the exact same recipe. Bake the cookies at the same temperature and for the same time. Only change the amount of salt in the recipe. Then measure the height or diameter of the cookies and decide whether to accept or reject the hypothesis.

Examples of Things That Are Not Experiments

Based on the examples of experiments, you should see what is not an experiment:

• Making observations does not constitute an experiment. Initial observations often lead to an experiment, but are not a substitute for one.
• Making a model is not an experiment.
• Neither is making a poster.
• Just trying something to see what happens is not an experiment. You need a hypothesis or prediction about the outcome.
• Changing a lot of things at once isn’t an experiment. You only have one independent and one dependent variable. However, in an experiment, you might suspect the independent variable has an effect on a separate. So, you design a new experiment to test this.

Types of Experiments

There are three main types of experiments: controlled experiments, natural experiments, and field experiments,

• Controlled experiment : A controlled experiment compares two groups of samples that differ only in independent variable. For example, a drug trial compares the effect of a group taking a placebo (control group) against those getting the drug (the treatment group). Experiments in a lab or home generally are controlled experiments
• Natural experiment : Another name for a natural experiment is a quasi-experiment. In this type of experiment, the researcher does not directly control the independent variable, plus there may be other variables at play. Here, the goal is establishing a correlation between the independent and dependent variable. For example, in the formation of new elements a scientist hypothesizes that a certain collision between particles creates a new atom. But, other outcomes may be possible. Or, perhaps only decay products are observed that indicate the element, and not the new atom itself. Many fields of science rely on natural experiments, since controlled experiments aren’t always possible.
• Field experiment : While a controlled experiments takes place in a lab or other controlled setting, a field experiment occurs in a natural setting. Some phenomena cannot be readily studied in a lab or else the setting exerts an influence that affects the results. So, a field experiment may have higher validity. However, since the setting is not controlled, it is also subject to external factors and potential contamination. For example, if you study whether a certain plumage color affects bird mate selection, a field experiment in a natural environment eliminates the stressors of an artificial environment. Yet, other factors that could be controlled in a lab may influence results. For example, nutrition and health are controlled in a lab, but not in the field.
• Bailey, R.A. (2008). Design of Comparative Experiments . Cambridge: Cambridge University Press. ISBN 9780521683579.
• di Francia, G. Toraldo (1981). The Investigation of the Physical World . Cambridge University Press. ISBN 0-521-29925-X.
• Hinkelmann, Klaus; Kempthorne, Oscar (2008). Design and Analysis of Experiments. Volume I: Introduction to Experimental Design (2nd ed.). Wiley. ISBN 978-0-471-72756-9.
• Holland, Paul W. (December 1986). “Statistics and Causal Inference”.  Journal of the American Statistical Association . 81 (396): 945–960. doi: 10.2307/2289064
• Stohr-Hunt, Patricia (1996). “An Analysis of Frequency of Hands-on Experience and Science Achievement”. Journal of Research in Science Teaching . 33 (1): 101–109. doi: 10.1002/(SICI)1098-2736(199601)33:1<101::AID-TEA6>3.0.CO;2-Z

Environmental Science Experiments

Studying the environment and how to overcome environmental problems is something every student should do. We all share this planet as our home, and it is up to all of us to become educated in the challenges facing it and how we need to change to protect it. Today we are sharing ideas for Environmental Science Experiments you can do with your students from elementary through high school.

Hands On Environmental Science for Students

What you will discover in this article!

Environmental Sciences was my original degree program when I first enrolled in University. I had always been passionate about wildlife management and conservation in particular, and it was my dream to work on protecting Canadian wildlife and their habitats as an environmental scientist. Sadly, after my second year I developed a number of severe health issues that forced me to change my degree program, but my passion for the environment has never waivered.

What is Environmental Science?

Environmental science is an interdisciplinary field. What does that mean? It simply means that it brings together a number of different disciplines and studies to focus on one area, the environment. Specifically it integrates physics, biology, chemistry, and geography, ecology, chemistry, plant science, zoology, mineralogy, oceanography, limnology, soil science, geology and physical geography, and atmospheric science. Certain environmental studies also integrate history, policy, politics, psychology, sociology and government studies. This is a very diverse field with a lot of demand as more and more we are focusing on finding ways to protect our planet.

Why is Environmental Science Important?

It is no secret, as societies have developed and grown throughout history, the impact on Earth and natural resources has not always been positive. For us to continue to develop and thrive on this planet it is important that we also focus on the environmental impacts of our actions.

Through environmental science studies, we see how our own health and the health of our environment are intertwined. We need to protect our planet to protect ourselves now and for future generations. Environmental science research and sustainable education for our students is crucial to keeping our ecosystems in balance, reversing damage done in the past, and preventing future damage and destruction.

Through environmental sciences we can find ways to continue to grow and thrive.

What do you learn in Environmental Sciences?

Environmental science is the study of nature, the environment, the planet, and everything living on this planet to identify and solve issues relating to the relationship we have with the natural world. It includes many subjects such as biology, chemistry, physics, geology, oceanography, zoology and many more types of science, in order to inform our understanding of the Earth and how to protect it.

As you can see this field is extremely broad, so there are many, many activities we can do with our kids that can fall under the umbrella of Environmental Sciences and so we can start fostering that passion to protect our planet.

Environmental Science Experiments and Activities for Kids

In order to make the environment a priority, it is important that we start incorporating it into our children’s education from an early age. One of the best ways I have found to help raise Earth conscience kids with an understanding of environmental issues is by doing hands on activities that really make an impact. We can start this at a very early age by incorporating simple nature and eco-friendly activities into our lessons, then as students grow and mature, we can start doing more advanced experiments.

To simplify things I have started with the most simple environmental activities for young kids first, then gradually increase the complexity of the activities until we reach experiments for high schoolers. The goal is to keep the lessons about the environment age appropriate and to foster that curiosity and passion for learning how to care for planet Earth.

Ready to dive into Environmental Sciences with your kids? Let’s go!

Nature Senses Detective

In this Nature Senses Detective activity young kids start to connect with nature using their senses. They start by going out into nature and intentionally and consciously use all of their senses to explore things in nature. Then, using items they discover in nature, have them see if they an identify the items by using only one sense.

Rewilding and Homemade Seed Bombs

Native seeding is a wonderful way to rewild areas that have been damaged due to human activity. They are also a lot of fun for kids to make and use. We have two different ways of making seed bombs , plus instructions for making seed paper . Don’t forget to make a seed bomb launcher !

Layers of the Earth Activity

Although Environmental Sciences tends to focus only on the crust and atmosphere of our planet, it is important to also understand the inner workings and layers of Earth. Our favourite activity for exploring this is to make beautiful Layers of the Earth Soap . We also have a version where kids can make a Layers of the Ocean soap for an Ocean Sciences study.

Sky Science

The sky is something we all can see every day, but the colours of the sky varies depending on where you are and what time of day it is. It can be vibrant blue or pale blue, pink, orange and even red. These colours are caused by light moving through the atmosphere. In this Sky Science experiment we explore how particles in the atmosphere affect what colours we see in the sky.

Oil Spill Activity – How to clean up oil on water

This is a very simple oil spill cleanup experiment , but one that teaches an important lesson about oil spills and pollution in our oceans and waterways. All you need is a bowl of water, some oil (vegetable or baby oil all work fine), and a variety of tools to try and clean up the oil. Then challenge your students to try and clean up the oil.

Water pollution and safety is a concern all over the world. In this Water Lab experiment students will collect samples from a variety of locally available water sources, then run some simple tests to compare the samples.

Water Pollution Experiment

Water pollution has a big effect on living beings. Whether it is plants or animals. If it is alive on this planet, it requires water. So when water becomes polluted it can have a big effect on life. In this Water Pollution experiment we explore the effect of water pollution on plant life.

Weather Science

The weather is a big part of the study of the environment. There are a number of ways you can study the weather. Some rain related activities would be doing a water cycle experiment , building a rain gauge or making a DIY barometer .

Renewable Energy Activity – Build a Windmill

This activity has a wonderful book you can incorporate into a unit study, The Boy Who Harnessed the Wind. It is a true story of a boy who taught himself how to build windmills to bring energy to his village. It is available in a variety of formats for all age ranges. Then challenge your kids to build their own windmill .

Natural Energy Sources – Building Food Batteries

A fun activity to do with kids is learning about natural energy sources, such as building batteries out of food. In the past we have built Potato Batteries , Lemon Batteries and even Pumpkin Batteries . This is a great way to get kids thinking differently about energy.

Making Bioplastics

Plastic is a huge issue all over the world when it comes to environmental concerns. As part of studies into plastic, have your students learn how to make bioplastics. It is an incredible way to get hands on with this complex subject. Learn how to make bioplastics with Milk Plastic or Gelatin Plastic .

Acid Rain Experiment

Acid rain is a major environmental concern across the planet. The impact of acid rain on various ecosystems is well documented, but it may be difficult for students to understand. In this acid rain science experiment we see the impact of acid rain on plants. The results are impactful and highly educational.

Greenhouse Effect Experiment

This Greenhouse Effect experiment is probably one of my favourite of all time that I did with my older kids. My kids often ask about climate change as they seek to better understand what is happening on our planet. In this experiment they were able to get hands on and develop a much greater understanding of the principles behind the Greenhouse Effect.

Studying the environment is a very important part of every child’s education. We all need to understand how our activities are impacting Earth and how we can lessen any damage we are causing. We also need more change makers in this area. Innovative and creative individuals who think outside of the box and will discover better ways to address the environmental issues affecting us all.

Want more activities learning about the Earth? Check out our comprehensive guide to Earth Day Activities for Kids .

5 Days of Smart STEM Ideas for Kids

Get started in STEM with easy, engaging activities.

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Experimentation

Watch this video to see what happens when you wring out a wet towel while floating in space..

The world of science is one of constant experimentation . But what does that word, experimentation , actually mean? Experimentation is the act or process of trying out a new procedure, idea, or activity. The scientists at the National Institute of Environmental Health Sciences do a lot of "experimenting" to determine how things in our environment affect our bodies. Their experiments help us determine what role environmental exposures and/or our unique genetic structures play with regard to human health. Armed with such knowledge, they may be able to discover some way to prevent that from happening.

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Games & puzzles, what's that word, scientific dictionary, not sure of what a word means.

What Is Environmental Science?

Dr. Frederic Beaudry is an associate professor of environmental science at Alfred University in New York.

• University of Maine
• Humboldt State University
• Université du Québec à Rimouski
• Natural Science
• Agriculture

Environmental science is the study of the interactions between the physical, chemical, and biological components of nature. As such, it is a multidisciplinary science: it involves a number of disciplines like geology, hydrology, soil sciences, plant physiology, and ecology. Environmental scientists may have training in more than one discipline; for example, a geochemist has expertise in both geology and chemistry. Most often, the multidisciplinary nature of environmental scientists’ work comes from collaborations they foster with other scientists from complementary research fields.

A Problem-Solving Science

Environmental scientists rarely just study natural systems, but instead usually work towards solving problems stemming from our interactions with the environment. Normally the basic approach taken by environmental scientists first involves using data to detect a problem and evaluate its extent. Solutions to the issue are then designed and implemented. Finally, monitoring is done to determine whether the problem was fixed. Some examples of the types of projects environmental scientists may be involved with include:

• Coordinating cleanup efforts at an abandoned oil refinery labeled as a Superfund site, determining the extent of the pollution problem and putting together a restoration plan.
• Forecasting the effects of global climate change and sea level rise on a coastal bay system, and assisting with finding solutions to limit damages on coastal wetlands, shoreline property, and public infrastructure.
• Consulting with a construction team to help them with minimizing sediment pollution coming from the site of a future grocery store.
• Assisting the managers of a state government’s fleet of vehicles with taking steps to reduce carbon dioxide and other greenhouse gas emissions.
• Designing a restoration plan to bring acreage of oak savanna in the proper ecological state to host the endangered Karner blue butterfly and its host plant, the blue lupine.

A Quantitative Science

To evaluate the condition of a field site, the health of an animal population, or the quality of a stream most scientific approaches require extensive data collection. That data then needs to be summarized with a suite of descriptive statistics, then used to verify if a particular hypothesis is supported or not. This type of hypothesis testing requires complex statistical tools. Trained statisticians are often part of large research teams to assist with complicated statistical models.

Other types of models are often used by environmental scientists. For example, hydrological models help understand groundwater flow and the spread of spilled pollutants, and spatial models implemented in a geographical information system (GIS) will help track deforestation and habitat fragmentation in remote areas.

An Education in Environmental Science

Whether it is a Bachelor of Arts (BA) or Bachelor of Science (BS), a university degree in environmental science can lead to a wide range of professional roles. Classes typically include earth science and biology courses, statistics, and core courses teaching sampling and analytical techniques specific to the environmental field. Students generally complete outdoor sampling exercises as well as inside laboratory work. Elective courses are usually available to provide students with the appropriate context surrounding environmental issues, including politics, economics, social sciences, and history.

Adequate university preparation for a career in environmental science can also take different paths. For example, a degree in chemistry, geology, or biology can provide a solid educational basis, followed by graduate studies in environmental science. Good grades in the basic sciences, some experience as an intern or summer technician, and positive letters of recommendation should allow motivated students to get into a Master’s program.

Environmental Science as a Career

Environmental science is practiced by people in a wide variety of sub-fields. Engineering firms employ environmental scientists to evaluate the condition of future project sites. Consulting companies can assist with remediation, a process where previously polluted soil or groundwater is cleaned up and restored to acceptable conditions. In industrial settings, environmental engineers use science to find solutions to limit the amount of polluting emissions and effluents. There are state and federal employees who monitor air, water, and soil quality to preserve human health.

The U.S. Bureau of Labor Statistics predicts an 11% growth in environmental science positions between the years 2016 and 2026. The median salary was $69,400 in 2017.

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An experiment is a set of actions designed to test a hypothesis. Experimentation is the key step in the Scientific Method because it provides tangible proof that a hypothesis is (probably) true or false.

Why experimentation is important

The Scientific Method

1. Observe a phenomenon that has no good explanation.

2. Formulate a hypothesis.

3. Design an experiment(s) to test the hypothesis.

4. Perform the experiment(s).

5. Accept, reject, or modify the hypothesis.

Once you understand the power of experimentation, and then pause to look at how much experimentation is behind most environmental sustainability problem solving proposals, you will be horrified. There's nearly none. Instead, nearly every article, book, and media appearance is based on the intuitive conclusions of its author. Should we pursue a Global Marshall Plan, as Al Gore argued in Earth in the Balance ? Or should we restructure society along the lines of what Natural Capitalism , by Hawken, Lovins, and Lovins, suggested? Or perhaps we should listen to those promoting sustainable development? Or what about Lester Brown's Eco-Economy , or Maurice Strong's Where on Earth Are We Going? , or Only One Earth: The care and maintenance of a small planet , by Barbara Ward and Rene Dubos? Which course is the one we should take? We can't take them all, because they differ.

The general root causes of a problem are the same no matter who performs the analysis. Thus effective solutions should be about the same. Whenever you encounter a gaggle of solutions that vary wildly, you can be certain that either all or all but one did not use root cause analysis .

What is the future of environmentalism?

Faced with an endless multitude of competing solutions like those listed above, what should we do?

That's the same question science faced for thousands of years: How can we determine what is truth and what it not? Science and scientists were totally unable to answer that question until recently, when the Scientific Method was perfected in the 17th century. After that the way forward was so clear, and so much easier to find, that the speed of scientific progress increased over a hundredfold.

The same could happen to the environmental movement if it changed from intuition to experimentation. The hypotheses to be tested all follow the same pattern: We should do so-and-so to solve this part of the problem.

Any environmentalist who is promoting a solution that is not based on formal analysis and experimentation is exactly where scientists were before they began using the Scientific Method. There were alchemists and quacks.

The right process, true analysis, and heavy experimentation lie at the heart of all efforts to solve extremely difficult problems. The ideas at Thwink.org are no exception. As promising as they may appear to be, they will never amount to much until they go through the Scientific Method's cycle of hypothesis, experimentation, and refinement of the hypothesis.

For more on experimentation, see the Wikipedia entries on experiment and critical experiment .

According to our good friend Wikipedia , “In the sciences, an experimentum crucis (English: crucial experiment or critical experiment) is an experiment capable of decisively determining whether or not a particular hypothesis or theory is superior to all other hypotheses or theories whose acceptance is currently widespread in the scientific community. In particular, such an experiment must typically be able to produce a result that rules out all other hypotheses or theories if true, thereby demonstrating that under the conditions of the experiment (i.e., under the same external circumstances and for the same "input variables" within the experiment), those hypotheses and theories are proven false but the experimenter's hypothesis is not ruled out.”

The biggest problem of the 20 th century was the environmental sustainability problem. The biggest experiment of that century was the hypothesis that popular solutions, which were all about the same from the perspective of Classic Activism , would solve the problem. They did not. The experiment showed the hypothesis to be false. It was the experimentum crucis of the 20 th century.

We are now well into the 21 st century. The same problem looms dead ahead as the world's biggest problem.

What solution strategy will the world's decision makers try this time, in their second experimentum crucis in a row?

Start your reading here:

Mastering the Science of Striking at the Root

Analysis is the breaking down of a problem into smaller easier to solve problems. Exactly how this is done determines the strength of your analysis.

You will see powerful techniques used in this analysis that are missing from what mainstream environmentalism has tried. This explains why a different outcome can be expected.

The key techniques are proper subproblem decomposition and root cause analysis .

The analysis was performed over a seven year period from 2003 to 2010. The results are summarized in the Summary of Analysis Results , the top of which is shown below:

Click on the table for the full table and a high level discussion of analysis results.

This is the solution causal chain present in all problems. Popular approaches to solving the sustainability problem see only what's obvious: the black arrows. This leads to using superficial solutions to push on low leverage points to resolve intermediate causes .

Popular solutions are superficial because they fail to see into the fundamental layer, where the complete causal chain runs to root causes . It's an easy trap to fall into because it intuitively seems that popular solutions like renewable energy and strong regulations should solve the sustainability problem. But they can't, because they don't resolve the root causes.

In the analytical approach, root cause analysis penetrates the fundamental layer to find the well hidden red arrow. Further analysis finds the blue arrow. Fundamental solution elements are then developed to create the green arrow which solves the problem. For more see Causal Chain in the glossary.

First the analysis divided the sustainability problem into four subproblems. Then each subproblem was individually analyzed. For an overview see The Four Subproblems of the Sustainability Problem .

This is no different from what the ancient Romans did. It’s a strategy of divide and conquer. Subproblems like these are several orders of magnitude easier to solve because you are no longer trying (in vain) to solve them simultaneously without realizing it. This strategy has changed millions of other problems from insolvable to solvable, so it should work here too.

For example, multiplying 222 times 222 in your head is for most of us impossible. But doing it on paper, decomposing the problem into nine cases of 2 times 2 and then adding up the results, changes the problem from insolvable to solvable.

Change resistance is the tendency for a system to resist change even when a surprisingly large amount of force is applied.

Overcoming change resistance is the crux of the problem, because if the system is resisting change then none of the other subproblems are solvable. Therefore this subproblem must be solved first. Until it is solved, effort to solve the other three subproblems is largely wasted effort.

The root cause of successful change resistance appears to be effective deception in the political powerplace. Too many voters and politicians are being deceived into thinking sustainability is a low priority and need not be solved now.

The high leverage point for resolving the root cause is to raise general ability to detect political deception. We need to inoculate people against deceptive false memes because once people are infected by falsehoods, it’s very hard to change their minds to see the truth.

Life form improper coupling occurs when two social life forms are not working together in harmony.

In the sustainability problem, large for-profit corporations are not cooperating smoothly with people. Instead, too many corporations are dominating political decision making to their own advantage, as shown by their strenuous opposition to solving the environmental sustainability problem.

The root cause appears to be mutually exclusive goals. The goal of the corporate life form is maximization of profits, while the goal of the human life form is optimization of quality of life, for those living and their descendents. These two goals cannot be both achieved in the same system. One side will win and the other side will lose. Guess which side is losing?

The high leverage point for resolving the root cause follows easily. If the root cause is corporations have the wrong goal, then the high leverage point is to reengineer the modern corporation to have the right goal.

Solution model drift occurs when a problem evolves and its solution model doesn’t keep up. The model “drifts” away from what’s needed to keep the problem solved.

The world’s solution model for solving important problems like sustainability, recurring wars, recurring recessions, excessive economic inequality, and institutional poverty has drifted so far it’s unable to solve the problem.

The root cause appears to be low quality of governmental political decisions. Various steps in the decision making process are not working properly, resulting in inability to proactively solve many difficult problems.

This indicates low decision making process maturity. The high leverage point for resolving the root cause is to raise the maturity of the political decision making process.

In the environmental proper coupling subproblem the world’s economic system is improperly coupled to the environment. Environmental impact from economic system growth has exceeded the capacity of the environment to recycle that impact.

This subproblem is what the world sees as the problem to solve. The analysis shows that to be a false assumption, however. The change resistance subproblem must be solved first.

The root cause appears to be high transaction costs for managing common property (like the air we breath). This means that presently there is no way to manage common property efficiently enough to do it sustainably.

The high leverage point for resolving the root cause is to allow new types of social agents (such as new types of corporations) to appear, in order to radically lower transaction costs.

There must be a reason popular solutions are not working.

Given the principle that all causal problems arise from their root causes, the reason popular solutions are not working (after over 40 years of millions of people trying) is popular solutions do not resolve root causes.

This is Thwink.org’s most fundamental insight.

Using the results of the analysis as input, 12 solutions elements were developed. Each resolves a specific root cause and thus solves one of the four subproblems, as shown below:

Click on the table for a high level discussion of the solution elements and to learn how you can hit the bullseye.

The solutions you are about to see differ radically from popular solutions, because each resolves a specific root cause for a single subproblem. The right subproblems were found earlier in the analysis step, which decomposed the one big Gordian Knot of a problem into The Four Subproblems of the Sustainability Problem .

Everything changes with a root cause resolution approach. You are no longer firing away at a target you can’t see. Once the analysis builds a model of the problem and finds the root causes and their high leverage points, solutions are developed to push on the leverage points.

Because each solution is aimed at resolving a specific known root cause, you can't miss. You hit the bullseye every time. It's like shooting at a target ten feet away. The bullseye is the root cause. That's why Root Cause Analysis is so fantastically powerful.

Nine Sample Solution Elements

1. Freedom from Falsehood

2. The Truth Test

3. Politician Truth Ratings

4. Politician Corruption Ratings

5. No Servant Secrets

6. Corporation 2.0 Suffix

7. Servant Responsibility Ratings

8. Sustainability Index

9. Quality of Life Index

The high leverage point for overcoming change resistance is to raise general ability to detect political deception. We have to somehow make people truth literate so they can’t be fooled so easily by deceptive politicians.

This will not be easy. Overcoming change resistance is the crux of the problem and must be solved first, so it takes nine solution elements to solve this subproblem. The first is the key to it all.

In this subproblem the analysis found that two social life forms, large for-profit corporations and people, have conflicting goals. The high leverage point is correctness of goals for artificial life forms. Since the one causing the problem right now is Corporatis profitis , this means we have to reengineer the modern corporation to have the right goal.

Corporations were never designed in a comprehensive manner to serve the people. They evolved. What we have today can be called Corporation 1.0. It serves itself. What we need instead is Corporation 2.0. This life form is designed to serve people rather than itself. Its new role will be that of a trusted servant whose goal is providing the goods and services needed to optimize quality of life for people in a sustainable manner.

Solution element: Corporation 2.0

What’s drifted too far is the decision making model that governments use to decide what to do. It’s incapable of solving the sustainability problem.

The high leverage point is to greatly improve the maturity of the political decision making process. Like Corporation 1.0, the process was never designed. It evolved. It’s thus not quite what we want.

The solution works like this: Imagine what it would be like if politicians were rated on the quality of their decisions. They would start competing to see who could improve quality of life and the common good the most. That would lead to the most pleasant Race to the Top the world has ever seen.

Solution element: Politician Decision Ratings

Presently the world’s economic system is improperly coupled to the environment. The high leverage point is allow new types of social agents to appear to radically reduce the cost of managing the sustainability problem.

This can be done with non-profit stewardship corporations. Each steward would have the goal of sustainably managing some portion of the sustainability problem. Like the way corporations charge prices for their goods and services, stewards would charge fees for ecosystem service use. The income goes to solving the problem.

Corporations gave us the Industrial Revolution. That revolution is incomplete until stewards give us the Sustainability Revolution.

Solution element: Common Property Rights

Cutting Through Complexity: The Engineer’s Guide to Solving Difficult Social Problems with Root Cause Analysis

This presents our research results, including SIP, analysis of the environmental sustainability problem, and twelve sample solution elements.

The Dueling Loops of the Political Powerplace: Why Progressives Are Stymied and How They Can Find Their Way Again

This analyzes the world’s standard political system and explains why it’s operating for the benefit of special interests instead of the common good. Several sample solutions are presented to help get you thwinking.

Change Resistance as the Crux (journal paper)

Solving Problems with Root Cause Analysis (journal paper)

Democratic Backsliding (working paper)

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• Introduction

Comparison with controlled study design

Natural experiments as quasi experiments, instrumental variables.

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natural experiment

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natural experiment , observational study in which an event or a situation that allows for the random or seemingly random assignment of study subjects to different groups is exploited to answer a particular question. Natural experiments are often used to study situations in which controlled experimentation is not possible, such as when an exposure of interest cannot be practically or ethically assigned to research subjects. Situations that may create appropriate circumstances for a natural experiment include policy changes, weather events, and natural disasters. Natural experiments are used most commonly in the fields of epidemiology , political science , psychology , and social science .

Key features of experimental study design include manipulation and control. Manipulation, in this context , means that the experimenter can control which research subjects receive which exposures. For instance, subjects randomized to the treatment arm of an experiment typically receive treatment with the drug or therapy that is the focus of the experiment, while those in the control group receive no treatment or a different treatment. Control is most readily accomplished through random assignment, which means that the procedures by which participants are assigned to a treatment and control condition ensure that each has equal probability of assignment to either group. Random assignment ensures that individual characteristics or experiences that might confound the treatment results are, on average, evenly distributed between the two groups. In this way, at least one variable can be manipulated, and units are randomly assigned to the different levels or categories of the manipulated variables.

In epidemiology, the gold standard in research design generally is considered to be the randomized control trial (RCT). RCTs, however, can answer only certain types of epidemiologic questions, and they are not useful in the investigation of questions for which random assignment is either impracticable or unethical. The bulk of epidemiologic research relies on observational data, which raises issues in drawing causal inferences from the results. A core assumption for drawing causal inference is that the average outcome of the group exposed to one treatment regimen represents the average outcome the other group would have had if they had been exposed to the same treatment regimen. If treatment is not randomly assigned, as in the case of observational studies, the assumption that the two groups are exchangeable (on both known and unknown confounders) cannot be assumed to be true.

As an example, suppose that an investigator is interested in the effect of poor housing on health. Because it is neither practical nor ethical to randomize people to variable housing conditions, this subject is difficult to study using an experimental approach. However, if a housing policy change, such as a lottery for subsidized mortgages, was enacted that enabled some people to move to more desirable housing while leaving other similar people in their previous substandard housing, it might be possible to use that policy change to study the effect of housing change on health outcomes. In another example, a well-known natural experiment in Helena , Montana, smoking was banned from all public places for a six-month period. Investigators later reported a 60-percent drop in heart attacks for the study area during the time the ban was in effect.

Because natural experiments do not randomize participants into exposure groups, the assumptions and analytical techniques customarily applied to experimental designs are not valid for them. Rather, natural experiments are quasi experiments and must be thought about and analyzed as such. The lack of random assignment means multiple threats to causal inference , including attrition , history, testing, regression , instrumentation, and maturation, may influence observed study outcomes. For this reason, natural experiments will never unequivocally determine causation in a given situation. Nevertheless, they are a useful method for researchers, and if used with care they can provide additional data that may help with a research question and that may not be obtainable in any other way.

The major limitation in inferring causation from natural experiments is the presence of unmeasured confounding. One class of methods designed to control confounding and measurement error is based on instrumental variables (IV). While useful in a variety of applications, the validity and interpretation of IV estimates depend on strong assumptions, the plausibility of which must be considered with regard to the causal relation in question.

In particular, IV analyses depend on the assumption that subjects were effectively randomized, even if the randomization was accidental (in the case of an administrative policy change or exposure to a natural disaster) and adherence to random assignment was low. IV methods can be used to control for confounding in observational studies, to control for confounding due to noncompliance, and to correct for misclassification.

IV analysis, however, can produce serious biases in effect estimates. It can also be difficult to identify the particular subpopulation to which the causal effect IV estimate applies. Moreover, IV analysis can add considerable imprecision to causal effect estimates. Small sample size poses an additional challenge in applying IV methods.

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Methodology

• What Is a Controlled Experiment? | Definitions & Examples

What Is a Controlled Experiment? | Definitions & Examples

Published on April 19, 2021 by Pritha Bhandari . Revised on June 22, 2023.

In experiments , researchers manipulate independent variables to test their effects on dependent variables. In a controlled experiment , all variables other than the independent variable are controlled or held constant so they don’t influence the dependent variable.

Controlling variables can involve:

• holding variables at a constant or restricted level (e.g., keeping room temperature fixed).
• measuring variables to statistically control for them in your analyses.
• balancing variables across your experiment through randomization (e.g., using a random order of tasks).

Table of contents

Why does control matter in experiments, methods of control, problems with controlled experiments, other interesting articles, frequently asked questions about controlled experiments.

Control in experiments is critical for internal validity , which allows you to establish a cause-and-effect relationship between variables. Strong validity also helps you avoid research biases , particularly ones related to issues with generalizability (like sampling bias and selection bias .)

• Your independent variable is the color used in advertising.
• Your dependent variable is the price that participants are willing to pay for a standard fast food meal.

Extraneous variables are factors that you’re not interested in studying, but that can still influence the dependent variable. For strong internal validity, you need to remove their effects from your experiment.

• Design and description of the meal,
• Study environment (e.g., temperature or lighting),
• Participant’s frequency of buying fast food,
• Participant’s familiarity with the specific fast food brand,
• Participant’s socioeconomic status.

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You can control some variables by standardizing your data collection procedures. All participants should be tested in the same environment with identical materials. Only the independent variable (e.g., ad color) should be systematically changed between groups.

Other extraneous variables can be controlled through your sampling procedures . Ideally, you’ll select a sample that’s representative of your target population by using relevant inclusion and exclusion criteria (e.g., including participants from a specific income bracket, and not including participants with color blindness).

By measuring extraneous participant variables (e.g., age or gender) that may affect your experimental results, you can also include them in later analyses.

After gathering your participants, you’ll need to place them into groups to test different independent variable treatments. The types of groups and method of assigning participants to groups will help you implement control in your experiment.

Control groups

Controlled experiments require control groups . Control groups allow you to test a comparable treatment, no treatment, or a fake treatment (e.g., a placebo to control for a placebo effect ), and compare the outcome with your experimental treatment.

You can assess whether it’s your treatment specifically that caused the outcomes, or whether time or any other treatment might have resulted in the same effects.

To test the effect of colors in advertising, each participant is placed in one of two groups:

• A control group that’s presented with red advertisements for a fast food meal.
• An experimental group that’s presented with green advertisements for the same fast food meal.

Random assignment

To avoid systematic differences and selection bias between the participants in your control and treatment groups, you should use random assignment .

This helps ensure that any extraneous participant variables are evenly distributed, allowing for a valid comparison between groups .

Random assignment is a hallmark of a “true experiment”—it differentiates true experiments from quasi-experiments .

Masking (blinding)

Masking in experiments means hiding condition assignment from participants or researchers—or, in a double-blind study , from both. It’s often used in clinical studies that test new treatments or drugs and is critical for avoiding several types of research bias .

Sometimes, researchers may unintentionally encourage participants to behave in ways that support their hypotheses , leading to observer bias . In other cases, cues in the study environment may signal the goal of the experiment to participants and influence their responses. These are called demand characteristics . If participants behave a particular way due to awareness of being observed (called a Hawthorne effect ), your results could be invalidated.

Using masking means that participants don’t know whether they’re in the control group or the experimental group. This helps you control biases from participants or researchers that could influence your study results.

You use an online survey form to present the advertisements to participants, and you leave the room while each participant completes the survey on the computer so that you can’t tell which condition each participant was in.

Although controlled experiments are the strongest way to test causal relationships, they also involve some challenges.

Difficult to control all variables

Especially in research with human participants, it’s impossible to hold all extraneous variables constant, because every individual has different experiences that may influence their perception, attitudes, or behaviors.

But measuring or restricting extraneous variables allows you to limit their influence or statistically control for them in your study.

Risk of low external validity

Controlled experiments have disadvantages when it comes to external validity —the extent to which your results can be generalized to broad populations and settings.

The more controlled your experiment is, the less it resembles real world contexts. That makes it harder to apply your findings outside of a controlled setting.

There’s always a tradeoff between internal and external validity . It’s important to consider your research aims when deciding whether to prioritize control or generalizability in your experiment.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Student’s  t -distribution
• Normal distribution
• Null and Alternative Hypotheses
• Chi square tests
• Confidence interval
• Quartiles & Quantiles
• Cluster sampling
• Stratified sampling
• Data cleansing
• Reproducibility vs Replicability
• Peer review
• Prospective cohort study

Research bias

• Implicit bias
• Cognitive bias
• Placebo effect
• Hawthorne effect
• Hindsight bias
• Affect heuristic
• Social desirability bias

In a controlled experiment , all extraneous variables are held constant so that they can’t influence the results. Controlled experiments require:

• A control group that receives a standard treatment, a fake treatment, or no treatment.
• Random assignment of participants to ensure the groups are equivalent.

Depending on your study topic, there are various other methods of controlling variables .

An experimental group, also known as a treatment group, receives the treatment whose effect researchers wish to study, whereas a control group does not. They should be identical in all other ways.

Experimental design means planning a set of procedures to investigate a relationship between variables . To design a controlled experiment, you need:

• A testable hypothesis
• At least one independent variable that can be precisely manipulated
• At least one dependent variable that can be precisely measured

When designing the experiment, you decide:

• How you will manipulate the variable(s)
• How you will control for any potential confounding variables
• How many subjects or samples will be included in the study
• How subjects will be assigned to treatment levels

Experimental design is essential to the internal and external validity of your experiment.

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Neighborhood environment and genetic risk for neurodevelopmental conditions: Interactive effects and influences on the stress response system

• Principal investigator: Meghan Miller. Psychiatry & Behavioral Sciences

The problem: This study explores the relationship between genetics and environment in the development of autism and ADHD. Both conditions have a genetic component, and there is growing recognition that shared genetic factors may increase the likelihood of each. This suggests the two conditions may share common developmental pathways. However, the extent to which the environment influences this genetic likelihood remains unclear. This is important because, unlike genetics, environmental factors may be more modifiable. This study focuses on two neighborhood-level factors: neighborhood disadvantage and air quality. We hypothesize that these factors may increase the likelihood of autism and ADHD in genetically susceptible infants by impacting their stress response system. 

The project: We will test these questions in 3 established cohorts of infants at high and low genetic likelihood for autism and/or ADHD based on family history. We will look at data on developmental functioning, physiological reactivity, and symptoms of autism and ADHD that was collected at 6/9, 12, 18, 24, and 36 months of age. Exposure to disadvantage and air pollution at the neighborhood level will be determined based on the infant’s home address in the first year of life. Findings from this research will help understand whether very young children at elevated genetic likelihood for autism or ADHD may be more susceptible to environmental influences than other children. This has large implications for reducing early childhood health disparities.

A Community-based One Health study on health effects of environmental harmful algal bloom toxin exposure

• Principal investigator: Wilson Rumbeiha. Environmental Health Toxicology

The problem: When certain species of algae bloom, they can release toxins that make people and animals ill. These are referred to as Harmful Algal Blooms (HABS) and are a major source of both ecological and human health risk around the world. Climate change increases these risks as higher temperatures can promote the growth of these algae. HABs produce microcystins and other types of toxins which can contaminate water and human and animal food webs. Chronic ingestion of these toxins can cause cancer and damage the liver, brain, kidney, skin, and/or the  immune system. Marginalized rural communities face the highest risk of drinking microcystin-contaminated water or food. There is currently no blood test for chronic exposure, and it is challenging to identify exposure pathways. 

The project: This project involves collaboration with the Big Valley Band of Pomo Indians (BVBPI) to study the impact of HABs from a “One Health” perspective, which highlights the interconnectedness of human and animal health. The project has two major goals. The first is to discover early biomarkers of chronic microcystin exposure in animals (mice and cattle). The second is to measure microcystins food webs (plants and animals)  of communities living in and around Clear Lake, one of the most impacted lakes in California. This study is intended as the beginning of a long-term collaboration with the BVBPI. Preliminary data will be used to apply for larger federal grants to advance this unique community-university collaboration to improve human, animal, and ecosystem health.

Wearable armband to monitor physiological indicators of heat stress

• Principal investigator: Cristina Davis, Mechanical and Aerospace Engineering
• Community partner: Central California Environmental Justice Network

The problem: Our rapidly warming climate presents serious public health risks, including heat stress and heat stroke. Many people are unaware of the early symptoms of heat stress, and this lack of knowledge can lead to injury or even death. 

As extreme heat events increase, wearable monitoring devices may play an important role in keeping vulnerable populations safe, but no such sensors are easily available. 

The project: Our team has developed a low-cost, lightweight armband that can record heart rate, oxygen saturation, activity level, skin temperature, and galvanic skin response (sweat). Its sensors continuously monitor these vitals to determine when the wearer is experiencing heat-related stress. 

This project will update the armband to include additional sensors and an alert function that will let the wearer and others know when they are experiencing heat stress, so that appropriate action can be taken.

If you'd like more information about a particular project, please contact Ruth Williams ( [email protected] ) for details.

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China accepts U.N. recommendations to improve environmental conflicts in Latin America

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• China was up for a Universal Periodic Review with the U.N. Human Rights Council, in which other member countries analyzed its actions abroad and provided recommendations to improve.
• Some of the most popular concerns were connected to the environmental and social conflicts affecting Latin America, including violence against activists, rushed impact studies and weak oversight of projects ranging from dams and highways to mines and bridges.
• China accepted a record ten out of 11 recommendations, giving hope to some that the country will change how it handles future projects in the region. But some critics are concerned that the country won’t keep its word.

It’s been a little over a decade since China launched its Belt and Road Initiative, a global program to improve relations with Latin America and other developing regions through trillions of dollars in investment in infrastructure and energy projects. But China hasn’t always carried out those projects in a responsible way, sparking outcry about their environmental impact and human rights violations, especially against Indigenous communities.

Recently, China was up for a Universal Periodic Review with the U.N. Human Rights Council, in which other member countries analyzed its actions abroad and provided recommendations to improve. Some of the most popular concerns have been emblematic of the environmental and social conflicts affecting Latin America, including violence against activists, rushed impact studies and weak oversight of projects ranging from dams and highways to mines and bridges.

China accepted a record ten out of 11 recommendations, giving hope to some that the country will change how it handles future projects in the region.

“China’s recognition of these problems is a crucial step towards accountability and transparency,” Paulina Garzón, director of Latin America Sustentable, said in a statement.

More than 200 civil society groups participated in the process, including a consortium from Latin America called the Collective on Chinese Financing and Investment, Human Rights and Environment (CICDHA), made up of groups from across the continent.

Ahead of the review, CICDHA analyzed 28 Chinese projects in Latin America and found that ten of them lacked a complete and thorough environmental impact assessment, suggesting that many companies break ground without fully understanding how to prevent pollution, limit carbon emissions and avoid destroying surrounding ecosystems.

One of the projects is the 90-megawatt Rucalhue hydropower plant in southern Chile, where Indigenous Mapuche-Pehuenche communities say they weren’t properly consulted about the impact it could have on the Bío Bío watershed.

Another is the San Carlos Panantza copper mine in Ecuador, made up of 13 mining blocks covering 41,000 hectares (101,313 acres), some of which overlaps with Shuar Arutam Indigenous land. Residents have expressed concern about pollution of the Zamora River.

China accepted the U.N. recommendation — officially submitted by Chile and Portugal — that the country pursue stronger legislation to protect peoples’ right to a clean, healthy and sustainable environment. This can be achieved by carrying out thorough studies before projects break ground, it said.

“We hope that accepting this recommendation by China will be a significant step towards having more rigorous environmental assessments, which include the effective participation of affected communities,” Lucio Cuenca, director of the Latin American Observatory of Environmental Conflicts, said after China’s decision.

China also accepted the recommendation that it create safer conditions for environmental and human rights defenders. Numerous projects across the region have been marked by violence against local communities speaking out against a wide range of issues, from pollution and deforestation to workers’ rights.

One of the most egregious cases involves the Las Bambas copper mine in southeastern Peru, where there were 72 complaints about human rights abuses between 2010 and 2023, according to the Business and Human Rights Resource Centre. Of the 72 complaints, 38 were attacks against people who opposed the mine.

In a similar recommendation, several countries asked that China take steps to ensure that its companies and financial institutions respect human rights abroad, including through more rigorous prior consultation processes and accountability measures.

“The lack of accessible and effective mechanisms has made it difficult for affected communities to file complaints and obtain redress for damages caused by Chinese companies and banks in the region,” said Sofía Jarrín of the Alliance of Human Rights Organizations, a coalition based in Ecuador.

While China’s acceptance of the recommendations can be viewed as a positive development, there’s no guarantee that it will follow through on its promises. The country accepted six similar recommendations during its last periodic review, and almost nothing has changed in that time, some critics say.

In some cases, including the Las Bambas mine in Peru, projects appeared in the previous review and then again this time around.

To ensure that the region sees change before the next periodic review in four years, CICDHA groups said Chinese embassies in Latin America should start acting as “formal channels” of communication between businesses, financial entities, the government and civil society. This will make it easier to address social and environmental conflicts before they escalate, they argued.

There also need to be better “repair and remediation” measures for negative impacts that have already taken place.

“This collaborative approach will not only allow for a better understanding of challenges and opportunities, but also ensure that the policies and measures adopted are inclusive, transparent and beneficial to all parties,” the groups said.

Banner image: A river runs next to the Mirador mine in Ecuador. Photo by Beth Wald.

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