testing hypothesis
CHAPTER
8
Introduction to
Hypothesis
Testing
8.1
Inferential Statistics and Hypothesis Testing
LEARNING OBJECTIVES
8.2 Four Steps to
Hypothesis Testing
After reading this chapter, you should be able to:
8.3
Hypothesis Testing and
Sampling Distributions
8.4
Making a Decision:
Types of Error
8.5
Testing a Research
Hypothesis: Examples
Using the z Test
8.6
Research in Focus:
Directional Versus
Nondirectional Tests
8.7
Measuring the Size of an Effect: Cohen’s d
8.8
Effect Size, Power, and
Sample Size
8.9
Additional Factors That
Increase Power
1 Identify the four steps of hypothesis testing.
2 Define null hypothesis, alternative hypothesis,
level of significance, test statistic, p value, and statistical significance.
3 Define Type I error and Type II error, and identify the type of error that researchers control.
4 Calculate the one-independent sample z test and interpret the results.
5 Distinguish between a one-tailed and two-tailed test, and explain why a Type III error is possible only with one-tailed tests.
6 Explain what effect size measures and compute a
Cohen’s d for the one-independent sample z test.
7 Define power and identify six factors that influence power.
8 Summarize the results of a one-independent sample z test in American Psychological Association (APA) format. 8.10 SPSS in Focus:
A Preview for
Chapters 9 to 18
8.11 APA in Focus:
Reporting the Test
Statistic and Effect Size
2
PART III: PROBABILITY AND THE FOUNDATIONS OF INFERENTIAL STATISTICS
8.1 INFERENTIAL STATISTICS AND HYPOTHESIS TESTING
We use inferential statistics because it allows us to measure behavior in samples to learn more about the behavior in populations that are often too large or inaccessi ble. We use samples because we know how they are related to populations. For example, suppose the average score on a standardized exam in a given
8
Introduction to
Hypothesis
Testing
8.1
Inferential Statistics and Hypothesis Testing
LEARNING OBJECTIVES
8.2 Four Steps to
Hypothesis Testing
After reading this chapter, you should be able to:
8.3
Hypothesis Testing and
Sampling Distributions
8.4
Making a Decision:
Types of Error
8.5
Testing a Research
Hypothesis: Examples
Using the z Test
8.6
Research in Focus:
Directional Versus
Nondirectional Tests
8.7
Measuring the Size of an Effect: Cohen’s d
8.8
Effect Size, Power, and
Sample Size
8.9
Additional Factors That
Increase Power
1 Identify the four steps of hypothesis testing.
2 Define null hypothesis, alternative hypothesis,
level of significance, test statistic, p value, and statistical significance.
3 Define Type I error and Type II error, and identify the type of error that researchers control.
4 Calculate the one-independent sample z test and interpret the results.
5 Distinguish between a one-tailed and two-tailed test, and explain why a Type III error is possible only with one-tailed tests.
6 Explain what effect size measures and compute a
Cohen’s d for the one-independent sample z test.
7 Define power and identify six factors that influence power.
8 Summarize the results of a one-independent sample z test in American Psychological Association (APA) format. 8.10 SPSS in Focus:
A Preview for
Chapters 9 to 18
8.11 APA in Focus:
Reporting the Test
Statistic and Effect Size
2
PART III: PROBABILITY AND THE FOUNDATIONS OF INFERENTIAL STATISTICS
8.1 INFERENTIAL STATISTICS AND HYPOTHESIS TESTING
We use inferential statistics because it allows us to measure behavior in samples to learn more about the behavior in populations that are often too large or inaccessi ble. We use samples because we know how they are related to populations. For example, suppose the average score on a standardized exam in a given