# Statistic

PROBLEM 4

Classified ads in the Ithaca Journal offered several used Toyota Corollas for sale. Listed

below are the ages of the cars and the advertised prices.

Age (yr) Price Advertised ($)

1 13,990

1 13,495

3 12,999

4 9,500

4 10,495

5 8,995

5 9,495

6 6,999

7 6,950

7 7,850

8 6,999

8 5,995

10 4,950

10 4,495

13 2,850

(a) Report the linear correlation coefficient value and comment on the form, the

direction, and strength of association between the age of a car and the advertised

price.

(b) Report the equation of the least-squares regression line. Interpret the coefficients.

(c) Report and interpret the value of the coefficient of determination.

(d) Carry out a T-test about correlation ( H1:p≠0). Use a 5% level of significance.

EXPECTATIONS

Draw graphs and charts when appropriate and necessary to demonstrate your

reasoning! Label all graphs and charts!

Display formulas. Write complete sentences to summarize your conclusions.

If use any table values, clearly state which tables you used (e.g. Table A-2, etc.).

You may attach your excel output when appropriate or necessary (e.g. a scatterplot,

etc.)

HYPOTHESIS TESTING QUESTIONS

Your work for all statistical hypothesis testing questions should include the following:

1. Established Ho and Ha.

2. Summary statistics (either computed or given in the problem)

3. The name of the test (e.g. 2sampleTtest or T-test about correlation, etc.)

4. A formula to compute a test statistic (e.g. 1Prop-Z test statistic, etc.)

5. A p-value of the test and/or a critical value from a statistical table.

6. Clearly state the decision rule you use the reach a conclusion. (You may have to

sketch a graph to show rejection regions.) Do you “Reject Ho” or do you “Fail to

Reject Ho”?

7. State your conclusion in plain language. Use complete sentences.

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xxxxxxxxxx xxx in xxx Ithaca xxxxxxx xxxxxxx several xxxx xxxxxx xxxxxxxx for sale. Listed

below xxx the ages xx xxx cars and the xxxxxxxxxx xxxxxxx

xxx xxxxxx the xxxxxx correlation coefficient value and comment on the xxxxx xxx

xxxxxxxxxx xxx xxxxxxxx xx association between xxx age xx a car and xxx xxxxxxxxxx

price.

xxx xxxxx of r= -0.98 xxxxx excel xxxxxxxxx xxx graph xxxx shows xx xxxxxxx relationship between xxx xxx price advertised. xx means as the age of car increases, xxx price xx xxxxxxxxxxxxx xxxxxxxxxx

The xxxx is xxxxxx xxxxxxxxx xxx xxxxxxxxx is opposite xxx xxx strength of association is xxxxxx inverse.

xxx xxxxxx xxx xxxxxxxx xx xxx xxxxxxxxxxxxx regression line. Interpret xxx xxxxxxxxxxxxx

xxxxxxxxxxxxxxx | xx xxxxx |

SD x= xxxxxxxx | SDy=5305.990064 |

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## Answer

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xxx **xxxxxxxxxxx xxxxx **

xxxxxx x year

y-axis = price**Correlation xxxxxxxxxxx**

(cov(X,Y)/s.d X x xxxx

= xxxxx

**xxx**

equation xx xxx least-squares regression line

xx a+bX

a=meanY- x xxxxx

xxxxxxxxxxxxx

b= -.971x (3.263/3220.542)

-959.045

a= 14285.9

14285.9-.959.045X

**xxx xxxxxx**

xxxxxxxxxxx of xxxxxxxxxxxxxx xxxxxxxxxxx xxxxxxxxxxxxx

xxxxxxx

xxxxxx