hypothesis testing in statistics slideshare

My presentations

Auth with social network:

Download presentation

We think you have liked this presentation. If you wish to download it, please recommend it to your friends in any social system. Share buttons are a little bit lower. Thank you!

Presentation is loading. Please wait.

Introduction To Hypothesis Testing

Published by ฐิติภรณ์ พันธุเมธา Modified over 5 years ago

Presentation on theme: "Introduction To Hypothesis Testing"— Presentation transcript:

Anthony Greene1 Simple Hypothesis Testing Detecting Statistical Differences In The Simplest Case:  and  are both known I The Logic of Hypothesis Testing:

Statistics 101 Class 8. Overview Hypothesis Testing Hypothesis Testing Stating the Research Question Stating the Research Question –Null Hypothesis –Alternative.

Statistical Significance What is Statistical Significance? What is Statistical Significance? How Do We Know Whether a Result is Statistically Significant?

Review: What influences confidence intervals?

Evaluating Hypotheses Chapter 9. Descriptive vs. Inferential Statistics n Descriptive l quantitative descriptions of characteristics.

Cal State Northridge  320 Ainsworth Sampling Distributions and Hypothesis Testing.

Statistical Significance What is Statistical Significance? How Do We Know Whether a Result is Statistically Significant? How Do We Know Whether a Result.

Chapter 3 Normal Curve, Probability, and Population Versus Sample Part 2.

Evaluating Hypotheses Chapter 9 Homework: 1-9. Descriptive vs. Inferential Statistics n Descriptive l quantitative descriptions of characteristics ~

Statistics for the Social Sciences Psychology 340 Fall 2006 Hypothesis testing.

C82MCP Diploma Statistics School of Psychology University of Nottingham 1 Overview of Lecture Independent and Dependent Variables Between and Within Designs.

Statistics for the Social Sciences Psychology 340 Spring 2005 Hypothesis testing.

8-2 Basics of Hypothesis Testing

PY 427 Statistics 1Fall 2006 Kin Ching Kong, Ph.D Lecture 6 Chicago School of Professional Psychology.

PSY 307 – Statistics for the Behavioral Sciences

Inferential Statistics

Statistics for the Social Sciences

Chapter 8 Introduction to Hypothesis Testing. Hypothesis Testing Hypothesis testing is a statistical procedure Allows researchers to use sample data to.

About project

Hypothesis Testing In Statistics | Hypothesis Testing Explained With Example |

Oct 06, 2021

220 likes | 230 Views

In this presentation, you are going to learn about Hypothesis Testing in Statistics. We will discuss the null hypothesis, the alternate hypothesis, the statistical significance of a hypothesis test, and more. This video breaks down these concepts into easy-to-understand chunks so you can grasp their meaning and applications. We'll also go over a real-world example near the end to show how these concepts are applied. Below topics will be covered in this Hypothesis Testing presentation: 1. What is Hypothesis Testing? 2. Research Question 3. Criteria for a good hypothesis 4. Null hypothesis

Share Presentation

Presentation Transcript

What’s in it for you? What is Hypothesis Testing? Research Question Hypothesis Criteria for Good Hypothesis Null Hypothesis Test Statistics Example Significance Level

What is Hypothesis Testing?

Click here to watch the video

What is Hypothesis Testing? Hypothesis tests are designed to statistically determine the probability whether a certain hypothesis would be considered accepted at a certain significance level or not The purpose of hypothesis testing is to check if there is enough statistical evidence in favor of a hypothesis

Research Question?

Research Question? • Research starts with a research question or hypothesis. • These are tentative generalization regarding a relationship between two or more variables. • There is a slight difference between the research question and the hypothesis. Hypothesis makes prediction about experimental outcome, research question does not.

Research Question? How many hours per day students spend on gaming? Do the college students with more study hours achieve higher GPAs than the students who do not put in more hours for study?

Hypothesis A hypothesis is a predictive statement, capable of being tested by scientific methods, that relates an independent variable to some dependent variable Hypothesis translates the research question into a prediction of expected outcomes How many hours per day students spend on gaming? Students who spend more time on gaming are socially alienated

Criteria For Good Hypothesis Should be compatible with current knowledge in the area It should follow logical consistency A good hypothesis must be stated briefly and clearly A hypothesis should be testable

Null Hypothesis

Null Hypothesis The null hypothesis (H0) is the logical alternative to the research hypothesis (H1) It is an assertion that we hold as true unless we have sufficient statistical evidence to conclude otherwise

Null Hypothesis Research Hypothesis:The duration of advertisement on TV channels is positively related to sales of that product Null Hypothesis: The duration of advertisement on TV channels is not related to the sales of that product

Test Statistics

Test Statistic A test statistic describes how closely the distribution of your data matches the distribution predicted under the null hypothesis of the statistical test you are using The test statistic summarizes your observed data into a single number using the central tendency, variation, sample size, and number of predictor variables in your statistical model

Test Statistic A t-test is a type of inferential statistic used to determine if there is a significant difference between the means of two groups, which may be related in certain features The F-test is designed to test if two population variances are equal. It does this by comparing the ratio of two variances. So, if the variances are equal, the ratio of the variances will be 1 A Z-test is a statistical measurement of a score's relationship to the mean in a group of scores

Example Consider a study on Science competency of a group of students who receive a special learning aid through online videos on Science It is hypothesized that this group after viewing the videos, will have scores on a standardized science test significantly different from those of the remainder of the population that has not seen the videos

Example Null HypothesisH0 Students who have received special Sciencelearning videoswill score high inSciencecompetencytest Research Hypothesis H = = Special sciencelearning videos make no impact on scores obtained inSciencecompetencytest

Significance Level The level of significance is the probability of rejecting the null hypothesis given it is true. It is the percentage risk of making a wrong decision. A significance level of 0.05 is often used in Hypothesis testing The level of significance is generally taken as 1%, 5%, 10% If the results of the study indicate a probability lower than the significance level; the researcher can reject the null hypothesis If the results of the study indicate a probability higher than the significance level; the researcher can support the null hypothesis

Join us to learn more! simplilearn.com UNITED STATES Simplilearn Solutions Pvt. Limited 201 Spear Street, Suite 1100 San Francisco, CA 94105 Phone: (415) 741-3319 INDIA Simplilearn Solutions Pvt. Limited #53/1C, 24th Main, 2nd Sector HSR Layout, Bangalore 560102 Phone: +91 8069999471 UNITED STATES Simplilearn Solutions Pvt. Limited 801 Corporate Center Drive, Suite 138 Raleigh, NC 27607 Phone: (919) 205-5565

More by User

Hypothesis Testing

Hypothesis Testing. Is It Significant?. Questions (1). What is a statistical hypothesis? Why is the null hypothesis so important? What is a rejection region? What does it mean to say that a finding is statistically significant ?

1.34k views • 23 slides

Testing Hypothesis

Testing Hypothesis. Nutan S. Mishra Department of Mathematics and Statistics University of South Alabama. Description of the problem. The population parameter(s) is unknown. Some one (say person A) has some claim about the value of this unknown parameter.

548 views • 24 slides

Hypothesis Testing. LIR 832 Lecture #3 January 30, 2007. Topics of the Day. A. Our Fundamental Problem Again: Learning About Populations from Samples B. Basic Hypothesis Testing: One Tailed Tests Using a Z Statistic C. Probability and Critical Cutoff Approaches: Really the Same Thing

2.77k views • 109 slides

Hypothesis Testing. Another inference method. We’ve used confidence intervals to give an estimate (with a margin of error) of m . We change the question we’re asking… from, “What’s an interval that likely encloses the parameter?”

737 views • 12 slides

Hypothesis Testing. Statistics for Microarray Data Analysis – Lecture 3 supplement The Fields Institute for Research in Mathematical Sciences May 25, 2002. p -values.

557 views • 28 slides

Hypothesis Testing:

Hypothesis Testing:. Inferential statistics. These will help us to decide if we should:. 1) believe that the relationship we found in our sample data is the same as the relationship we would find if we tested the entire population. OR.

822 views • 39 slides

Inferential Statistics: Hypothesis Testing

Inferential Statistics: Hypothesis Testing. Test of Categorical Data / Proportion. Inferential Statistics. Estimation Estimate population means Estimate population proportion Estimate population variance Hypothesis testing Testing population means Testing categorical data / proportion

133 views • 0 slides

Hypothesis testing

Hypothesis testing. Null hypothesis Ho - this hypothesis holds that if the data deviate from the norm in any way, that deviation is due strictly to chance. Alternative hypothesis Ha - the data show something important.

701 views • 47 slides

Hypothesis Testing. Overview. This is the other part of inferential statistics, hypothesis testing Hypothesis testing and estimation are two different approaches to two similar problems Estimation is the process of using sample data to estimate the value of a population parameter

1.76k views • 126 slides

Hypothesis Testing. Martina Litschmannová m artina.litschmannova @vsb.cz K210. Terms Introduce in Prior Chapter. Population … all possible values Sample … a portion of the population Statistical inference … generalizing from a sample to a population with calculated degree of certainty

1.07k views • 37 slides

Hypothesis Testing. An Inference Procedure We will study procedures for both the unknown population mean on a quantitative variable and the unknown population proportion on a qualitative variable. Background .

359 views • 18 slides

Hypothesis testing. Dr David Field. Summary. Null hypothesis and alternative hypothesis Statistical significance (p-value, alpha level) One tailed and two tailed predictions What is a true experiment? random allocation to conditions Outcomes of experiments Type I and Type II error

863 views • 39 slides

Hypothesis Testing. Chapter 9 BA 201. Hypothesis Testing. The null hypothesis , denoted by H 0 , is a tentative assumption about a population parameter. The alternative hypothesis , denoted by H a , is the opposite of what is stated in the null hypothesis.

734 views • 41 slides

Inferential Statistics: Hypothesis Testing. Testing Population Variances Analysis of Variance – ANOVA. Content. Estimation Estimate population means Estimate population proportion Estimate population variance Hypothesis testing Testing population means

1.22k views • 67 slides

Hypothesis Testing. Hypothesis Testing. Hypothesis is a claim or statement about a property of a population. Hypothesis Testing is to test the claim or statement Example : A conjecture is made that “the average starting salary for computer science gradate is Rs 45,000 per month”.

1.05k views • 40 slides

Inferential Statistics: Hypothesis Testing. Hypothesis Testing Testing Population Means. Inferential Statistics. Estimation Estimate population means Estimate population proportion Estimate population variance Hypothesis testing Testing population means

1.13k views • 82 slides

Hypothesis Testing. Philo I Group 3. What is a Hypothesis?. a tentative assumption made in order to draw out and test its logical/analytic or empirical consequences. Problems. Roots of Hypotheses Typical setting for hypothesis formation Can be anything.

375 views • 13 slides

Hypothesis Testing. Developing Null and Alternative Hypotheses. Type I and Type II Errors. Population Mean: s Known. Population Mean: s Unknown. Developing Null and Alternative Hypotheses. Hypothesis testing can be used to determine whether

926 views • 69 slides

Hypothesis testing. Make assumptions. One of them is the “hypothesis.” Calculate the probability of what happened based on the assumptions. If the probability of what happened is too low, reject the hypothesis. Coin. Assumption: The probability of heads is ½. One toss possibilities:

298 views • 12 slides

Hypothesis Testing. Hypothesis Testing. Greene: App. C:892-897 Statistical Test: Divide parameter space ( Ω ) into two disjoint sets: Ω 0 , Ω 1 Ω 0 ∩ Ω 1 =  and Ω 0  Ω 1 = Ω

807 views • 38 slides

Medical Statistics: Hypothesis Testing

Medical Statistics: Hypothesis Testing. Nimrod Lavi, MD Adhir Shroff, MD, MPH. Agenda. Types of variables Descriptive statistics What is a hypothesis Definition of a p-value Sample vs. universe Comparative statistics T-tests Chi-square. Agenda. Types of variables

826 views • 56 slides

Hypothesis Testing Example

Hypothesis Testing Example. Test the claim that the true mean # of TV sets in US homes is equal to 3. (Assume σ = 0.8). 1-2. State the appropriate null and alternative hypotheses H 0 : μ = 3 H 1 : μ ≠ 3 (This is a two tailed test)

1.58k views • 14 slides

hypothesis testing in statistics slideshare

IMAGES

VIDEO