1 / 33

Chapter 9 Introduction to the t Statistic

Chapter 9 Introduction to the t Statistic. PowerPoint Lecture Slides Essentials of Statistics for the Behavioral Sciences Seventh Edition by Frederick J Gravetter and Larry B. Wallnau. Chapter 9 Learning Outcomes. Concepts to review. Sample standard deviation (Chapter 4)

Download Presentation

Chapter 9 Introduction to the t Statistic

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Chapter 9Introduction to the t Statistic PowerPoint Lecture SlidesEssentials of Statistics for the Behavioral SciencesSeventh Editionby Frederick J Gravetter and Larry B. Wallnau

  2. Chapter 9 Learning Outcomes

  3. Concepts to review • Sample standard deviation (Chapter 4) • Degrees of freedom (Chapter 4) • Standard error (Chapter 7) • Hypothesis testing (Chapter 8)

  4. 9.1 The t Statistic: Alternative to z • Sample mean (M) approximates population mean (μ) • Standard error describes how much difference is reasonable to expect between M and μ.

  5. z-score statistic • Use z-score statistic to quantify inferences about the population. • Use unit normal table to find the critical region if z-scores form a normal distribution • When n≥ 30 or • When the original distribution is approximately normally distributed

  6. Problem with z-scores • The z-score requires more information than researchers typically have available • Requires knowledge of the population standard deviation σ • Researchers usually have only the sample data available

  7. Estimated standard error • Use s2 to estimate σ2 • Estimated standard error: • Estimated standard error is used as estimate of the real standard error when the value of σm is unknown.

  8. The t-Statistic • The t-statistic uses the estimated standard error in place of σm • The t statistic is used to test hypotheses about an unknown population mean μ when the value of σ is also unknown

  9. Degrees of freedom • Computation of sample variance requires computation of the sample mean first. • Only n-1 scores in a sample are independent • Researchers call n-1the degrees of freedom • Degrees of freedom • Noted as df • df = n-1

  10. Figure 9.1 Distributions of the t statistic

  11. The t Distribution • Family of distributions, one for each value of degrees of freedom. • Approximates the shape of the normal distribution • Flatter than the normal distribution • More spread out than the normal distribution • More variability (“fatter tails”) in t distribution • Use Table of values of t in place of the Unit Normal Table for hypothesis tests.

  12. Figure 9.2 The t distribution for n=3

  13. 9.2 Hypothesis tests with the t statistic • Null hypothesis for one-sample t test statistic

  14. Figure 9.3 Basic experimental situation for t statistic

  15. Four steps for hypothesis testing • State the null and alternative hypothesesSelect an alpha level • Locate the critical region using the t distribution table and df • Calculate the t test statistic • Make a decision regarding H0

  16. Figure 9.4 Critical region in the tdistribution for α = .05 and df = 8.

  17. Assumptions of the t test • Values in the sample are independent observations. • The population sampled must be normal. • With large samples, this assumption can be violated without affecting the validity of the hypothesis test.

  18. Learning Check • When n is small (less than 30), the t distribution ______.

  19. Learning Check - Answer • When n is small (less than 30), the t distribution ______.

  20. Learning Check • Decide if each of the following statements is True or False.

  21. Answer

  22. 9.3 Measuring Effect Size • Hypothesis test determines whether the treatment effect is greater than chance • No measure of the size of the effect is included • A very small treatment effect can be statistically significant • Results from a hypothesis test should be accompanied by a measure of effect size

  23. Cohen’s d • Original equation included population parameters • Estimated Cohen’s d is computed using the sample standard deviation

  24. Figure 9.5 Distribution for Examples 9.1 and 9.2

  25. Percentage of variance explained • Determining the amount of variability in scores explained by the treatment effect is an alternative method for measuring effect size. • r2= 0.01 small effect • r2= 0.09 medium effect • r2= 0.25 large effect

  26. Figure 9.6 Deviations with and without the treatment effect

  27. 9.4 Directional Hypotheses and One-tailed Tests • Non-directional test is more commonly used • Directional test may be used for particular research situations • Four steps of hypothesis test are carried out • The critical region is defined in just one tail of the t distribution.

  28. Figure 9.7 Critical region in the t curve for one-tailed test

  29. Learning Check • The results of a hypothesis test are reported as follows: t(21) = 2.38, p < .05. What was the statistical decision and how big was the sample?

  30. Learning Check - Answer • The results of a hypothesis test are reported as follows: t(21) = 2.38, p < .05. What was the statistical decision and how big was the sample?

  31. Learning Check • Decide if each of the following statements is True or False.

  32. Answer

More Related