Age Value 3.8 14280 2.4 12050 7 4300 9. 3298 1.2. 16350 12.5 1280 15.7 990 18.2 280 0.6 18250 20.9. 320 11 2300 7 5200 21. 180 6 6420 1 15250 6.4. 8500 4.1 12500 3.1 14000 5.4. 9200 7.3. 5120 4 10250 8 4320 9.7 3080 1.8 14050 10.2 3220

You are to conduct a correlation and regression analysis on the data set in Project1Data which contains two variables called Age and Value. This data is based on a random sample of twenty five Nissan car owners. The variable Age represents the age of the car in years and the variable Value represents the current value of the car in dollars.

What you must submit is the following:

All eleven questions must be answered typed up in a word file and converted into a pdf. You can

also copy & paste the results from the session window and graph(s) from StatCrunch directly into

Word.

Also state: An introduction, explanation/interpretation of your analysis,

and a conclusion. It is best to provide as many details as possible.

1) What are the explanatory and response variables?

2) Determine the mean, standard deviation, and five-number summary for each variable.

3) What is the value of the linear correlation coefficient?

4) Based on the value of the linear correlation coefficient, is the correlation between Age and Value strong or weak? Why?

5) Determine the equation of the linear regression line.

6) Use your regression equation to predict the Value of a Nissan if the Age is ten years old.

7) Generate a scatterplot with a fitted regression line.

8) Interpret the meaning of the slope of the regression line in terms of Age and Value.

9) What is the y-intercept of the regression line and what does it mean regarding Age and Value? Is this realistic?

10) Use your regression equation to predict the Value of a Nissan if the Age is one hundred thirty years old. Is this realistic?

11) What is the value of the coefficient of determination and what does it mean regarding this data set?