Statistical Application: Inferential Statistics
Statistical Application: Inferential Statistics
**NEED: Someone good with Statistics and has the SPSS software!!!!
For this discussion, answer each of the questions below. Remember to answer all of the questions listed. Answer the questions in complete sentences and number each question to correspond with the question number in the text. Remember to place all answers in APA style, and pay special attention to technical notations and formatting. Please see the attached file of Chapters 5, 6 and 7 of the text.
Complete question 27 in Chapter 5, “End of Chapter Problem,” pages 148–151. Provide a rationale for each of your answers.
Complete questions 11 and 21 in Chapter 6, “End of Chapter Problems,” pages 175–177. Provide a rationale for each of your answers.
Complete questions 27 and 29 in Chapter 7, “End of Chapter Problems,” pages 208–210. Provide a rationale for each of your answers.
Discuss any successes, shortcuts, challenges, or difficulties you had when completing the problems.
Chapter 5
- The inaccuracy of lie detection. Maureen O’Sullivan (2007) stated that research on expert lie detection is “based on three assumptions: 1) Lie detection is an ability that can be measured; 2) This ability is distributed like many other abilities (i.e., normally); 3) Therefore, only a very few people will be highly accurate” (p. 118). How does this researcher know that very few people will be highly accurate at lie detection?
Chapter 6
- What does the standard error measure?
- State whether each of the following statements is true or false. If false, then explain what would make the statement true.
(a) The central limit theorem explains why the mean is always at the center of a distribution.
(b) The standard error of the mean is the standard deviation of a sampling distribution of sample means.
(c) The mean of a sampling distribution is equal to the population mean from which samples are selected.
Chapter 7
- As α increases, so does the power to detect an effect. Why, then, do we restrict α from being larger than .05?
- Directional versus nondirectional hypothesis testing. Cho and Abe (2013) provided a commentary on the appropriate use of one-tailed and two-tailed tests in behavioral research. In their discussion, they outlined the following hypothetical null and alternative hypotheses to test a research hypothesis that males self-disclose more than females:
H0: µmales − µfemales ≤ 0
H1: µmales − µfemales > 0
(a) What type of test is set up with these hypotheses, a directional test or a nondirectional test?
(b) Do these hypotheses encompass all possibilities for the population mean? Explain.
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