1. The Graduate Record Exam (GRE) has a combined verbal and quantitative mean of 1000 and a standard deviation of 200. Scores range from 200 to 1600 and are approximately normally distributed. For each of the following problems:

(a) draw a rough sketch, darkening in the portion of the curve that relates to the answer, and
(b) indicate the percentage or score called for by the problem.

a. What percentage of the persons who take the test score above 1300?
b. What percentage score above 800?
c. What percentage score below 1200?
d. Above what score do 20% of the test-takers score?
e. Above what score do 30% of the test-takers score?

2. For the data presented below, answer the questions that follow.

Score on political Score on current
Individual awareness test events test
1 24 23
2 16 12
3 11 11
4 9 6
5 8 13
6 14 11
7 17 16
8 19 16
9 21 21
10 25 25
11 18 11
12 13 13
13 11 14
14 6 10
15 9 10
16 12 7
a. Construct a scatterplot.
b. Draw a regression line through the data point that "fits" the data points reasonably well.
c. Enclose the data points with a ellipse.
d. Estimate the direction of the correlation.
e. Estimate the strength of the correlation coefficient.
f. Now, use only the data points associated with current event scores of 15 and lower and indicate the effects this has on the direction and strength of the correlation coefficient.
g. Explain why this is the case.
h. Explain in words what a non-truncated scatterplot means.
i. Identify how likely it is that a causal relationship has been indicated.

Solution Summary

The solution gives detailed steps on answering a series of questions on two topices: normally distributed data and simple regression.

Simple Linear Regressionand Multiple Regression.
I'd like to ask whether you think multiple regression (the use of more IV's) is always better than simpleregression? Why or why not?
What problems may exist with multiple regression that are not an issue for simple linear regression?

I was wondering if someone could help explain the NormalDistribution to me, maybe in more simple terms. An example would also be useful. I am using the program Minitab to generate my answers to questions.

Please make up a simpleregression analysis "application" example.
For the "application" example submit both your manual and excel stats functional work for testing hypothesis H0: beta 1=0 (by using t test).
A typical simpleregression analysis "application" example is as follows: The following data are the height, in inches,

I am working to develop an equation for Y that is based on up to 10 different X variables. I am trying multiple regression. What I need to know is what tests I run to determine the suitability of the model? For example how do I determine if simple, linear regression is suitable or if I need to try a different, non-linear form?

This problem has to be done in Excel.
Prepare a forecast, using simple linear regression, for each quarter of the next year from the following past 2 years' quarterly sales information.
Quarter Sales
1----- 160
2----- 195
3----- 150
4----- 140
5----- 215
6----- 240
7----- 205
8----- 190

When is understanding the normaldistributionand the factors that affect its shape important in solving business and marketing-related questions? Explain with a simple example.

If the t ratio for the slope of a simple linear regression equation is equal to 1.614 and the critical value of the t distribution at the 1% and 5% levels of significance, respectively, are 3.499 and 2.365 is the slope:
not significantly different from zero
significantly different from zero at both the 1% and 5% levels
sign

For the y and x values listed in file XR15066, obtain the simple linear regression equation, then analyze the residuals by (a) constructing a histogram, (b) using a normal probability plot, (c) plotting the residuals versus the x values and (d) plotting the residuals versus the order in which they were observed. Do any of the as