2. The data below are the final exam scores of 10 randomly selected statistics students and the number of hours they studied for the exam. Find the equation of the regression line for the given data. Predict the final exam score when a student studied for 4 hours. Predict the final exam score when a student studied for 6 hours.

3. A manager wishes to determine the relationship between the number of miles (in hundreds of miles) the manager's sales representatives travel per month and the amount of sales (in thousands of dollars) per month. Find the equation of the regression line for the given data. Predict the value of sales when the sales representative travel 8 miles. Predict the value of sales when the sales representative traveled 11 miles.

miles traveled, x 2 3 10 7 8 15 3 1 11
Sales, y 31 33 78 62 65 61 48 55 120

4. Find the correlation coefficient between X and Y. Is there a weak or strong, positive or negative linear correlation between X and Y?

5. The data below are the final exam scores of 10 randomly selected statistics students and the number of hours they studied for the exam. Find the correlation coefficient between hours studied and final exam scores. Is there a weak or strong, positive or negative correlation between hours studied and final exam scores?

Data from a study of 534 U.S. workers from 1985 includes information about each worker's hourly wage (measured in U.S. dollars/hour) and age (measured in years). First, linearregression is performed to estimate the relationship between hourly wage and age (years), and the resulting slope of age is 0.08, and correlation coeffici

QUESTIONS:
(a) How does correlationanalysis differ from regressionanalysis?
(b) What does a correlationcoefficient reveal?
(c) State the quick rule for a significant correlation and explain its limitations.
(d) What sums are needed to calculate a correlationcoefficient?
(e) What are the two ways of testing a correlati

You are interested in finding out if a student's ACT score is a good predictor of their final college grade point average (GPA). You have obtained the following data and are going to conduct a regressionanalysis. What is the best fit to conduct this analysis?
ACT | GPA
22.0 | 3.0
32.0 | 3.78
33.0 | 3.68
21.0 | 2.94
27

The test scores of 6 randomly picked students and the numbers of hours they prepared are as follows:
Hours: 5 10 4 6 10 9
Score: 64 86 69 86 59 87
The equation of the regression line is y(^on top)=1.06604x+67.3491. Find the coefficient of determination.

1. Testing for a linearCorrelation:
Use the scatterplot and the linearcorrelationcoefficient r to determine whether there is a correlation between the two variables.
x 1 2 2 5 6
y 2 5 4 15 15
2. Finding the Equation of the Regression Line:
Use the given data to find the equation of the regression line.
x 1 2

Theory of regression:
How does regression relate to linear algebra?
Regression terms and symbols:
What is the difference between strong negative and strong positive?
Practical examples of regressionanalysis:
When would you use regressioncorrelation at a place of employment, or in education, or in politics?
Interpre

The city of Oakdale wishes to see if there is a linear relationship between the temperature and the amount of electricity used (in kilowatts). Based on the data in the table below, is there a significant linear relationship between temperature and the amount of electricity used?
Temperature (x) 73 78 85 98 93 81 76 105
Kil

Please help with the following problem. Provide step by step calculations.
Construct a scatterplot for the (x, y) values below, and answer the following questions.
x y
1 -10.0
2 -20.0
3 -30.0
4 -40.0
5 -50.0
Q