This assignment consists of 3 separate questions (Q1, Q2, Q3) that respectively relate to Pearson corelation, chi-square corelation, and bivariate regression. By doing these data analytical questions, you will develop the understanding of key concepts such as coefficients and the violation of assumption. You will also demonstrate competency to perform appropriate data analysis using PASW program.

1. In your Warner text, see Chapter 7, page 307, Question 14 and answer the following:
   • Suppose that two raters (rater A and rater B) each assign physical attractiveness scores (0 = not at all attractive to 10 = extremely attractive) to a set of 7 facial photographs. Pearson r is a common index of inter-rater reliability or agreement on quantitative ratings. A correlation of +1 would indicate perfect rank order agreement between raters, while an r of 0 would indicate no agreement about judgments of relative attractiveness. Generally r’ s of .8 to .9 are considered desirable when reliability is assessed.
     • Compute the Pearson correlation between the Rater A/Rater B attractiveness ratings. What is the obtained r value?
     • Is your obtained r statistically significant? (Unless otherwise specified, use a = .05 two tailed for all significance tests).
     • Are the rater A and rater B scores "reliable"? Is there good or poor agreement between raters?

Solution: The following results are obtained from SPSS:

The correlation for Rater A and Rater B is r = 0.809. This correlation is significant at the 0.05 significance level, because the corresponding p-value is p = 0.028 < 0.05.

The scores obtained are considered reliable, because the correlation is greater than 0.8.

1. In your Warner text, see Chapter 8, page 337, Question 7 and answer the following: When the Titanic capsized, was there a difference in the probability of being saved for women passengers in first class versus women passengers in third class? There were a total of 309 women in first and third class. The relevant numbers appear on page 337 of the Warner text.
   • Compute a phi coefficient using the observed cell frequencies in the table above.
   • Also compute a chi-square statistic for the observed frequencies in the table above.
   • Write up your results in paragraph form. Was there a statistically significant association between being in first class and being saved, when we look at the passenger survival data from the Titanic? How strong was the association between being in first class and being saved (versus being in third class and being lost)?
2. To complete this question, use the data from Table 9.2 on page 375 of your Warner text which shows GNP per capita (X), and mean life satisfaction, for a set of 19 nations (Y). Enter the data into PASW.

• Run the <Analyze><Descriptives> procedure; obtain the mean and standard deviation for each variable.
• Do appropriate preliminary data screening, then run the bivariate regression to predict life satisfaction from GNP. Write up the results in paragraph form including: statistical significance, effect size, and nature of relationship. Use the Save command to save the unstandardized residuals as a new variable in your SPSS worksheet. Include effect size and nature of relationship even if the regression is not statistically significant.
• Using the <Transform> <Compute> command, create a new variable that tells you the squared unstandardized residual for each case. Using the <Descriptives> command, obtain the sum of the squared residuals across all 19 cases. Note that this total for sum of square residuals should correspond to SS _residual in the ANOVA table in your PASW regression printout.
• Show that you can use the sums of squares in the ANOVA table in the PASW printout to reproduce the value of R ² on the PASW printout.

Price: $17.22

Solution: The downloadable solution consists of 9 pages, 822 words and 3 charts.
Deliverable: Word Document