(BQ) Part 2 book "Statistics for the behavioral sciences" has contents: Testing means - The related samples t-Test; estimation and confidence intervals; linear regression and multiple regression; nonparametric tests - Chi-Square tests;.and other contents. | Testing Means One-Sample and Two-IndependentSample t Tests • • • Learning Objectives After reading this chapter, you should be able to: I. 2. Explain why a t distribution is associated with n - 1 degrees of freedom and describe the information that is conveyed by the t statistic. Calculate the degrees of freedom for a onesample t test and a two-independent-sample t test, and locate critical values in the t table. 3. Identify the assumptions for the one-sample t test. 4. Compute a one-sample t test and interpret the results. 5. Compute effect size and proportion of variance for a one-sample t test. 6. Identify the assumptions for the twoindependent-sample t test. 7. Compute a two-independent-sample ttest and interpret the results. 8. Compute effect size and proportion of variance for a two-independent-sample t test. 9. Summarize the results of a one-sample t test and a two-independent-sample t test in APA format. I0. Compute a one-sample t test and a twoindependent-sample t test using SPSS. Chapter 9 : Te sting Means 265 GOING FROM ZTO t In the discussion of hypothesis testing in Chapter 8, we introduced the one-sample z test. To compute the test statistic for a one-sample z test, we must know the value of the population variance. However, it is rare in behavioral science that we know the variance of a population, in which case we cannot compute the z statistic: Z obt M-fl h = - - , W ere 0 M cr = ,-. crM ; n To compute this z statistic formula, we need to know the population standard deviation, which requires that we know the variance. If we do not know the population variance, then we cannot compute the value for z. We need an alternative test statistic that can be computed when the population variance is unknown. An alternative to the z statistic was proposed by William Sealy Gosset (Student, 1908), a scientist working with the Guinness brewing company to improve brewing processes .
