SECTION A:

Q#1. The formula for a regression equation is Y' = 3X - 2. What would be the predicted Y score for a person scoring 4 on X?

Q#2. Suppose it is possible to predict a person's score on Test B from the person's score on Test A. The regression equation is: B' = 2.3A + 9.5. What is a person's predicted score on Test B assuming this person got a 40 on Test A?

Q#3.Last year, five randomly selected students took a math aptitude test before they began their statistics course in Statistics Department of Raily University. These students' math aptitude test scores (in x_i column) and statistics achievement scores (in y_i column) at the end of the course are tabulated below:

Student	Math aptitude test scores (xi)	Statistics achievement scores (yi)
1	95	85
2	85	95
3	80	70
4	70	65
5	60	70

The Statistics Department has three questions.

• What linear regression equation best predicts statistics performance, based on math aptitude scores?
• If a student made an 80 on the aptitude test, what score would we expect her to make in statistics?
• How well does the regression equation fit the data?

SECTION B:

Q#4. For what type of data in a research is a chi-square statistics of hypothesis testing appropriate?

Q#5. Imagine that you sample 12 scores from a standard normal distribution, square each score, and sum the squares. How many degrees of freedom does the Chi Square distribution that corresponds to this sum have (asking for computing dffor Chi Square statistics)?

Q#6. What is the mean of a Chi Square distribution with 8 degrees of freedom?

Q#7. A student is interested in whether there is a relationship between Gender and Major at her college. In conducting this research, she randomly sampled some men and women on campus and asked them if their major was part of the natural sciences (NS), social sciences (SS), or humanities (H). Her results appear in the table below.