Tests of Significance: The Basics

Slides:



Advertisements
Similar presentations
Introduction to Hypothesis Testing
Advertisements

AP Statistics – Chapter 9 Test Review
Probability & Statistical Inference Lecture 7 MSc in Computing (Data Analytics)
July, 2000Guang Jin Statistics in Applied Science and Technology Chapter 9_part I ( and 9.7) Tests of Significance.
Tests of significance Confidence intervals are used when the goal of our analysis is to estimate an unknown parameter in the population. A second goal.
BCOR 1020 Business Statistics Lecture 21 – April 8, 2008.
Chapter 9 Hypothesis Testing.
BCOR 1020 Business Statistics Lecture 20 – April 3, 2008.
Significance Tests for Proportions Presentation 9.2.
CHAPTER 2 Statistical Inference 2.1 Estimation  Confidence Interval Estimation for Mean and Proportion  Determining Sample Size 2.2 Hypothesis Testing:
More About Significance Tests
+ Chapter 9 Summary. + Section 9.1 Significance Tests: The Basics After this section, you should be able to… STATE correct hypotheses for a significance.
Topic 7 - Hypothesis tests based on a single sample Sampling distribution of the sample mean - pages Basics of hypothesis testing -
Agresti/Franklin Statistics, 1 of 122 Chapter 8 Statistical inference: Significance Tests About Hypotheses Learn …. To use an inferential method called.
Lecture 16 Section 8.1 Objectives: Testing Statistical Hypotheses − Stating hypotheses statements − Type I and II errors − Conducting a hypothesis test.
S-012 Testing statistical hypotheses The CI approach The NHST approach.
Introduction to Inferece BPS chapter 14 © 2010 W.H. Freeman and Company.
McGraw-Hill/Irwin Copyright © 2007 by The McGraw-Hill Companies, Inc. All rights reserved. Chapter 8 Hypothesis Testing.
Economics 173 Business Statistics Lecture 4 Fall, 2001 Professor J. Petry
Tests of Significance: The Basics BPS chapter 15 © 2006 W.H. Freeman and Company.
1 CHAPTER 4 CHAPTER 4 WHAT IS A CONFIDENCE INTERVAL? WHAT IS A CONFIDENCE INTERVAL? confidence interval A confidence interval estimates a population parameter.
Math 4030 – 9a Introduction to Hypothesis Testing
Logic and Vocabulary of Hypothesis Tests Chapter 13.
What is a Test of Significance?. Statistical hypotheses – statements about population parameters Examples Mean weight of adult males is greater than 160.
© Copyright McGraw-Hill 2004
Tests of Significance: The Basics ESS chapter 15 © 2013 W.H. Freeman and Company.
Major Steps. 1.State the hypotheses.  Be sure to state both the null hypothesis and the alternative hypothesis, and identify which is the claim. H0H0.
Testing a Single Mean Module 16. Tests of Significance Confidence intervals are used to estimate a population parameter. Tests of Significance or Hypothesis.
THE MORE T-DISTRIBUTION & SIGNIFICANCE TESTING FOR QUANTITATIVE DATA CHAPTER 23.
Chapter 9: Hypothesis Tests for One Population Mean 9.2 Terms, Errors, and Hypotheses.
Hypothesis Tests Hypothesis Tests Large Sample 1- Proportion z-test.
A.P. STATISTICS EXAM REVIEW TOPIC #2 Tests of Significance and Confidence Intervals for Means and Proportions Chapters
Hypothesis Testing Involving One Population Chapter 11.
+ Homework 9.1:1-8, 21 & 22 Reading Guide 9.2 Section 9.1 Significance Tests: The Basics.
Comparing Two Proportions
CHAPTER 9 Testing a Claim
Chapter 9 Hypothesis Testing.
8-1 of 23.
Math 4030 – 9b Introduction to Hypothesis Testing
CHAPTER 9 Testing a Claim
Chapters 20, 21 Hypothesis Testing-- Determining if a Result is Different from Expected.
Comparing Two Proportions
Hypothesis Tests for 1-Sample Proportion
Hypothesis Testing: Hypotheses
Tests of significance: The basics
More about Tests and Intervals
Chapter 9 Testing A Claim
Week 11 Chapter 17. Testing Hypotheses about Proportions
Hypothesis Tests for a Population Mean in Practice
CHAPTER 17: Tests of Significance: The Basics
Section 11.2: Carrying Out Significance Tests
Chapter Review Problems
Inferences on Two Samples Summary
Chapter 9 Hypothesis Testing.
Chapter 9: Hypothesis Testing
Statistical inference
Elementary Statistics
HYPOTHESIS TESTS ABOUT THE MEAN AND PROPORTION
CHAPTER 12 Inference for Proportions
STA 291 Spring 2008 Lecture 18 Dustin Lueker.
CHAPTER 12 Inference for Proportions
More About Tests Notes from
CHAPTER 9 Testing a Claim
CHAPTER 9 Testing a Claim
Chapter 9: Testing a Claim
CHAPTER 9 Testing a Claim
CHAPTER 9 Testing a Claim
CHAPTER 9 Testing a Claim
Chapter 16 Single-Population Hypothesis Tests
Statistical inference
Presentation transcript:

Tests of Significance: The Basics BPS chapter 15 © 2006 W.H. Freeman and Company

Statistical significance A consumer advocate is interested in evaluating the claim that a new granola cereal contains “4 ounces of cashews in every bag.” The advocate recognizes that the amount of cashews will vary slightly from bag to bag, but she suspects that the mean amount of cashews per bag is less than 4 ounces. To check the claim, the advocate purchases a random sample of 40 bags of cereal and calculates a sample mean of 3.68 ounces of cashews. What is the size of the observed effect? 3.68 oz. -3.68 oz. 4 – 3.68 = 0.32 oz. 3.68 – 4 = - 0.32 oz.

Statistical significance (answer) A consumer advocate is interested in evaluating the claim that a new granola cereal contains “4 ounces of cashews in every bag.” The advocate recognizes that the amount of cashews will vary slightly from bag to bag, but she suspects that the mean amount of cashews per bag is less than 4 ounces. To check the claim, the advocate purchases a random sample of 40 bags of cereal and calculates a sample mean of 3.68 ounces of cashews. What is the size of the observed effect? 3.68 oz. -3.68 oz. 4 – 3.68 = 0.32 oz. 3.68 – 4 = - 0.32 oz.

Statistical significance A consumer advocate is interested in evaluating the claim that a new granola cereal contains “4 ounces of cashews in every bag.” The advocate recognizes that the amount of cashews will vary slightly from bag to bag, but she suspects that the mean amount of cashews per bag is less than 4 ounces. To check the claim, the advocate purchases a random sample of 40 bags of cereal and calculates a sample mean of 3.68 ounces of cashews. The consumer advocate should declare statistical significance only if there is a small probability of Observing a sample mean of 3.68 oz. or less when  = 4 oz. Observing a sample mean of exactly 3.68 oz. when  = 4 oz. Observing a sample mean of 3.68 oz. or greater when  = 4 oz. Observing a sample mean of less than 4 oz. when  = 4 oz.

Statistical significance (answer) A consumer advocate is interested in evaluating the claim that a new granola cereal contains “4 ounces of cashews in every bag.” The advocate recognizes that the amount of cashews will vary slightly from bag to bag, but she suspects that the mean amount of cashews per bag is less than 4 ounces. To check the claim, the advocate purchases a random sample of 40 bags of cereal and calculates a sample mean of 3.68 ounces of cashews. The consumer advocate should declare statistical significance only if there is a small probability of Observing a sample mean of 3.68 oz. or less when  = 4 oz. Observing a sample mean of exactly 3.68 oz. when  = 4 oz. Observing a sample mean of 3.68 oz. or greater when  = 4 oz. Observing a sample mean of less than 4 oz. when  = 4 oz.

Statistical significance A consumer advocate is interested in evaluating the claim that a new granola cereal contains “4 ounces of cashews in every bag.” The advocate recognizes that the amount of cashews will vary slightly from bag to bag, but she suspects that the mean amount of cashews per bag is less than 4 ounces. To check the claim, the advocate purchases a random sample of 40 bags of cereal and calculates a sample mean of 3.68 ounces of cashews. Suppose the consumer advocate computes the probability described in the previous question to be 0.0048. Her result is Statistically significant. Not statistically significant.

Statistical significance (answer) A consumer advocate is interested in evaluating the claim that a new granola cereal contains “4 ounces of cashews in every bag.” The advocate recognizes that the amount of cashews will vary slightly from bag to bag, but she suspects that the mean amount of cashews per bag is less than 4 ounces. To check the claim, the advocate purchases a random sample of 40 bags of cereal and calculates a sample mean of 3.68 ounces of cashews. Suppose the consumer advocate computes the probability described in the previous question to be 0.0048. Her result is Statistically significant. Not statistically significant.

Statistical significance A consumer advocate is interested in evaluating the claim that a new granola cereal contains “4 ounces of cashews in every bag.” The advocate recognizes that the amount of cashews will vary slightly from bag to bag, but she suspects that the mean amount of cashews per bag is less than 4 ounces. To check the claim, the advocate purchases a random sample of 40 bags of cereal and calculates a sample mean of 3.68 ounces of cashews. If the probability described in the previous question is 0.0048, the difference between the observed value and the hypothesized value is Small. Large.

Statistical significance (answer) A consumer advocate is interested in evaluating the claim that a new granola cereal contains “4 ounces of cashews in every bag.” The advocate recognizes that the amount of cashews will vary slightly from bag to bag, but she suspects that the mean amount of cashews per bag is less than 4 ounces. To check the claim, the advocate purchases a random sample of 40 bags of cereal and calculates a sample mean of 3.68 ounces of cashews. If the probability described in the previous question is 0.0048, the difference between the observed value and the hypothesized value is Small. Large.

Statistical significance A consumer advocate is interested in evaluating the claim that a new granola cereal contains “4 ounces of cashews in every bag.” The advocate recognizes that the amount of cashews will vary slightly from bag to bag, but she suspects that the mean amount of cashews per bag is less than 4 ounces. To check the claim, the advocate purchases a random sample of 40 bags of cereal and calculates a sample mean of 3.68 ounces of cashews. If the probability described in the previous question is 0.0048, then the consumer advocate should conclude that the granola is Correctly labeled. Incorrectly labeled.

Statistical significance (answer) A consumer advocate is interested in evaluating the claim that a new granola cereal contains “4 ounces of cashews in every bag.” The advocate recognizes that the amount of cashews will vary slightly from bag to bag, but she suspects that the mean amount of cashews per bag is less than 4 ounces. To check the claim, the advocate purchases a random sample of 40 bags of cereal and calculates a sample mean of 3.68 ounces of cashews. If the probability described in the previous question is 0.0048, then the consumer advocate should conclude that the granola is Correctly labeled. Incorrectly labeled.

Stating hypotheses A consumer advocate is interested in evaluating the claim that a new granola cereal contains “4 ounces of cashews in every bag.” The advocate recognizes that the amount of cashews will vary slightly from bag to bag, but she suspects that the mean amount of cashews per bag is less than 4 ounces. To check the claim, the advocate purchases a random sample of 40 bags of cereal and calculates a sample mean of 3.68 ounces of cashews. What alternative hypothesis does she want to test?

Stating hypotheses (answer) A consumer advocate is interested in evaluating the claim that a new granola cereal contains “4 ounces of cashews in every bag.” The advocate recognizes that the amount of cashews will vary slightly from bag to bag, but she suspects that the mean amount of cashews per bag is less than 4 ounces. To check the claim, the advocate purchases a random sample of 40 bags of cereal and calculates a sample mean of 3.68 ounces of cashews. What alternative hypothesis does she want to test?

Statistical significance We reject the null hypothesis whenever P-value > . P-value  . P-value  . P-value  .

Statistical significance (answer) We reject the null hypothesis whenever P-value > . P-value  . P-value  . P-value  .

Statistical significance The significance level is denoted by    P-value

Statistical significance (answer) The significance level is denoted by    P-value

Statistical significance Which of the following is a conservative choice for significance level? 0.01 0.25 0.50 0.75 1

Statistical significance (answer) Which of the following is a conservative choice for significance level? 0.01 0.25 0.50 0.75 1

Calculating P-values To calculate the P-value for a significance test, we need to use information about the Sample distribution Population distribution Sampling distribution of

Calculating P-values (answer) To calculate the P-value for a significance test, we need to use information about the Sample distribution Population distribution Sampling distribution of

Conclusions Suppose the P-value for a hypothesis test is 0.304. Using  = 0.05, what is the appropriate conclusion? Reject the null hypothesis. Reject the alternative hypothesis. Do not reject the null hypothesis. Do not reject the alternative hypothesis.

Conclusions (answer) Suppose the P-value for a hypothesis test is 0.304. Using  = 0.05, what is the appropriate conclusion? Reject the null hypothesis. Reject the alternative hypothesis. Do not reject the null hypothesis. Do not reject the alternative hypothesis.

Conclusions Suppose the P-value for a hypothesis test is 0.0304. Using  = 0.05, what is the appropriate conclusion? Reject the null hypothesis. Reject the alternative hypothesis. Do not reject the null hypothesis. Do not reject the alternative hypothesis.

Conclusions (answer) Suppose the P-value for a hypothesis test is 0.0304. Using  = 0.05, what is the appropriate conclusion? Reject the null hypothesis. Reject the alternative hypothesis. Do not reject the null hypothesis. Do not reject the alternative hypothesis.

P-value True or False: The P-value should be calculated BEFORE choosing the significance level for the test. True False

P-value (answer) True or False: The P-value should be calculated BEFORE choosing the significance level for the test. True False

Conclusions Suppose a significance test is being conducted using a significance level of 0.10. If a student calculates a P-value of 1.9, the student Should reject the null hypothesis. Should fail to reject the null hypothesis. Made a mistake in calculating the P-value.

Conclusions (answer) Suppose a significance test is being conducted using a significance level of 0.10. If a student calculates a P-value of 1.9, the student Should reject the null hypothesis. Should fail to reject the null hypothesis. Made a mistake in calculating the P-value.

Stating hypotheses If we test H0:  = 40 vs. Ha:  < 40, this test is One-sided (left tail). One-sided (right tail). Two-sided.

Stating hypotheses (answer) If we test H0:  = 40 vs. Ha:  < 40, this test is One-sided (left tail). One-sided (right tail). Two-sided.

Stating hypotheses If we test H0:  = 40 vs. Ha:   40, this test is One-sided (left tail). One-sided (right tail). Two-sided.

Stating hypotheses (answer) If we test H0:  = 40 vs. Ha:   40, this test is One-sided (left tail). One-sided (right tail). Two-sided.

Using CIs to test A researcher is interested in estimating the mean yield (in bushels per acre) of a variety of corn. From her sample, she calculates the following 95% confidence interval: (118.74, 128.86). Her colleague wants to test (at  = 0.05) whether or not the mean yield for the population is different from 120 bushels per acre. Based on the given confidence interval, what can the colleague conclude? The mean yield is different from 120 and it is statistically significant. The mean yield is not different from 120 and it is statistically significant. The mean yield is different from 120 and it is not statistically significant. The mean yield is not different from 120 and it is not statistically significant.

Using CIs to test (answer) A researcher is interested in estimating the mean yield (in bushels per acre) of a variety of corn. From her sample, she calculates the following 95% confidence interval: (118.74, 128.86). Her colleague wants to test (at  = 0.05) whether or not the mean yield for the population is different from 120 bushels per acre. Based on the given confidence interval, what can the colleague conclude? The mean yield is different from 120 and it is statistically significant. The mean yield is not different from 120 and it is statistically significant. The mean yield is different from 120 and it is not statistically significant. The mean yield is not different from 120 and it is not statistically significant.