Reference no: EM13901184

Question 1. The following table presents the total sample size and the percentage distribution of a grouped variable, "Hours of Shopping this Year." Calculate the mean and the variance. Note that you need to find "frequency (fi)", "midpoint (Yi)", and "deviation (di)" for each row before you can get the mean and the variance.

Hours Shopping	Percentage (%)	Frequency (fi)	Midpoint (Yi)	Deviation di = Yi -Y	di2	di2(fi)
1-4	5
5-8	25
9-12	15
13-16	30
17-20	5
21-24	20
Total	100.0	550

Question 2. One of the Stat's TA's believes that cats are more popular than dogs. Test the hypothesis using the data within the data tables provided below.

Cats

Popularity	Freq	Percent	Cum. %
low	15	75	75
high	5	25	100

Total: 20

Dogs

Popularity	Freq	Percent	Cum. %
low	22	68.75	68.75
high	10	45.45	100

Total: 32

1: State the research and null hypothesis in symbolic form.

2: Perform a T-test.

3: Find the critical value of T relative to the .05 alpha level.

4: Make a decision relative to the null hypothesis and interpret the result.

Question 3. The following equation is a predicted regression line based on an analysis of a sample of 2,500 people. "Happiness" is the dependent continuous variable measured by a 100 point happiness scale. Income is a dummy variable, 0 for low-income, 1 for middle-income, and 2 for upper-income.

Happiness = a + b * Income

Here is the STATA output:

Happiness	Coefficient	St. Error	t	P>t
Income	22.45	4.76	7.65	.000
Constant	19.1	4.09	2.25	.029

Observations = 2500 F(1, 2498) = 13.32 Prob> F=.0001 R^2 = .217 Adj. R^2= .201

Answer the following questions.

1. Are the variables happiness and income related, and if so, by how much? How do you know this?

2. What is the strength of this relationship?

Happiness = a + b * Income+ b * Health - b * Age

The above equation is a predicted multivariable regression line based on an analysis of a sample of 2,500 people. "Happiness" is the dependent continuous variable measured by a 100 point happiness scale. Health is a continuous measure, scored 0 (poor health) to 10 (excellent health). Income is a dummy variable, 0 for low-income, 1 for middle- to upper-income. Age is a continuous measure and is measured in years.

Here is the STATA.

Happiness	Coefficient	St. Error	t	P>t
Income	15.6	3.76	3.65	.001
Health	10.4	1.77	3.09	.001
Age	-5.9	.87	2.76	.01
Constant	19.1	4.09	2.25	.029

Observations = 2500 F(1, 2498) = 9.44 Prob> F= .0001 R^2 = .381 Adj. R^2= .341

Answer the following.

3. Compare the coefficients from this model to the bivariate model above. How are they different, and why do you think they are different? Which is a better model?

4. Write the predicted equations for both the bivariate and multivariate regressions. Use variable names instead of x and y.

5. Your friend is planning on making a New Year's resolution to be happier next year. What would you recommend her to focus on?

Question 4. The following table depicts data about the relationship between hours played per week on a video game (Y) and experience level growth in the game (x).

	Hours playing video game per week	Experience level growth in game	Mean	S.D.
Hours playing video game per week	1.00	.88	21.2	3.9
Experience level growth in game		1.00	9	2.3
N = 154

1. Find the coefficients.

R =

b =

β =

2. Find the constant.

a =

3. Find the equation.

Y ¯=

4. Fill out the table for ANOVA for Regression

	Sum of Squares	Degrees of freedom	Mean Squares	F-statistic
Regression
Error
Total

Interpret the result of the F-statistic: can you reject the null at the alpha level of .05?