Find the regression equation. Find the selling price of a home with an area of 2,200 square feet. Construct a 95% confidence interval for all 2,200 square foot homes. Construct a 95% prediction interval for the selling price of a home with 2,200 square feet.

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Answer 1

Question

Compare Compare Correlation is the measure of the degree of the relationship between the variables. In regression, the relationship between the variables to predict one by another is assessed. In correlation there is no cause and effect between the variables, whereas in regression there is a cause and effect between the variables. By using correlation, we cannot predict anything, but regression is a predictive tool. Coefficients are symmetrical in correlation but in regression they are asymmetrical. Correlation is independent of change in origin and scale, but regression is not independent of change in scale.

Chapter 13, Problem 62DE

a.

To determine

Find the regression equation.

Find the selling price of a home with an area of 2,200 square feet.

Construct a 95% confidence interval for all 2,200 square foot homes.

Construct a 95% prediction interval for the selling price of a home with 2,200 square feet.

a.

Expert Solution

Answer to Problem 62DE

The regression equation is y^=64.7931+0.0703x.

The selling price of a home with an area of 2,200 square feet is $219,429.30.

The 95% confidence interval for all 2,200 square foot homes is (210,882.70,227,975.90)

The 95% prediction interval for the selling price of a home with 2,200 square feet is (131,837.60, 307,021.0)

Explanation of Solution

Here, the selling price is the dependent variable and size of the home is the independent variable.

Step-by-step procedure to obtain the ‘regression equation’ using MegaStat software:

In an EXCEL sheet enter the data values of x and y.
Go to Add-Ins > MegaStat > Correlation/Regression > Regression Analysis.
Select input range as ‘Sheet1!$B$2:$B$106’ under Y/Dependent variable.
Select input range ‘Sheet1!$A$2:$A$106’ under X/Independent variables.
Select ‘Type in predictor values’.
Enter 2,200 as ‘predictor values’ and 95% as ‘confidence level’.
Click on OK.

Output obtained using MegaStat software is given below:

STAT TECHNIQUES IN BUSI 2370 >CI<, Chapter 13, Problem 62DE , additional homework tip 1

From the regression output, the regression equation is as follows.

y^=64.7931+0.0703x.

Where y is the selling price and x is the size of the home.

The selling price of a home with an area of 2,200 square feet is $219,429.30.

The 95% confidence interval for all 2,200 square foot homes is (210,882.70,227,975.90)

The 95% prediction interval for the selling price of a home with 2,200 square feet is (131,837.60, 307,021.0)

b.

To determine

Find the regression equation.

Find the selling price of a home with 20 miles from the center of the city.

Construct a 95% confidence interval for homes with 20 miles from the center of the city.

Construct a 95% prediction interval a home with 20 miles from the center of the city.

b.

Expert Solution

Answer to Problem 62DE

The regression equation is y^=270.1670−3.3540(x).

The estimated selling price of a home with 20 miles from the center of the city is $203087.10.

The 95% confidence interval for homes with 20 miles from the center of the city is

(190,267.40,215,906.80)

The 95% prediction interval for homes with 20 miles from the center of the city is

(114,117.8,292,056.5)

Explanation of Solution

Step-by-step procedure to obtain the ‘regression equation’ using MegaStat software:

In an EXCEL sheet enter the data values of x and y.
Go to Add-Ins > MegaStat > Correlation/Regression > Regression Analysis.
Select input range as ‘Sheet1!$C$2:$C$106’ under Y/Dependent variable.
Select input range ‘Sheet1!$B$2:$B$106’ under X/Independent variables.
Select ‘Type in predictor values’.
Enter 20 as ‘predictor values’ and 95% as ‘confidence level’.
Click on OK.

Output obtained using MegaStat software is given below:

STAT TECHNIQUES IN BUSI 2370 >CI<, Chapter 13, Problem 62DE , additional homework tip 2

From the above output, the regression equation is as follows:

y^=270.1670−3.3540(x)

Where y is the selling price of a home and x is the distance from the center of the city.

The estimated selling price of a home with 20 miles from the center of the city is $203087.10.

The 95% confidence interval for homes with 20 miles from the center of the city is (190,267.40,215,906.80)

The 95% prediction interval for a home with 20 miles from the center of the city is

(114,117.8,292,056.5)

c.

To determine

Check whether there is a negative correlation between “distance from the center of the city” and “selling price” using 0.05 significance level.

Check whether there is a positive correlation between the “area of the home” and “selling price” using 0.05 significance level.

Report the p-value of the test and summarize the results.

c.

Expert Solution

Answer to Problem 62DE

There is a negative association between “distance from the center of the city” and “selling price”.

There is a positive association between “selling price” and “area of the home”.

Explanation of Solution

Denote the population correlation as ρ.

The null and alternative hypotheses are stated below:

Null hypothesis:

H0:ρ≥0

That is, the correlation between “distance from the center of the city” and “selling price” is greater than or equal to zero.

Alternative hypothesis:

H1:ρ<0

That is, the correlation between “distance from the center of the city” and “selling price” is less than zero.

Here, the sample size is 105 and the correlation coefficient between “distance from the center of the city” and “selling price” is –0.347.

The test statistic is as follows:

t=−0.347105−21−(−0.347)2=−0.347×1030.9378=−3.75

Thus, the test statistic value is –3.75.

The degrees of freedom is as follows:

df=n−2=105−2=103

The level of significance is 0.05. Therefore, 1−α=0.95.

Critical value:

Step-by-step software procedure to obtain the critical value using EXCEL software:

Open an EXCEL file.
In cell A1, enter the formula “=T.INV (0.95, 103)”.

Output obtained using EXCEL is given as follows:

STAT TECHNIQUES IN BUSI 2370 >CI<, Chapter 13, Problem 62DE , additional homework tip 3

Decision rule:

Reject the null hypothesis H₀, if |t|-calculated> |t|-critical value. Otherwise, fail to reject H₀.

Conclusion:

The value of test statistic is –3.75 and the critical value is 1.659.

Here, |t|-calculated(=3.75)> |t|-critical value(1.659).

By the rejection rule, reject the null hypothesis.

Thus, it can be concluded that there is a negative association between“distance from the center of the city” and “selling price”.

Calculation of p-value:

Using excel formula = T.DIST (–3.75,103,TRUE)

STAT TECHNIQUES IN BUSI 2370 >CI<, Chapter 13, Problem 62DE , additional homework tip 4

The p-value of the test is 0.000.

Check the correlation between independent variables “area of the home” and “selling price” is positive:

The hypotheses are given below:

Null hypothesis:

H0:ρ≤0

That is, the correlation between “size of the home” and “selling price” is less than or equal to zero.

Alternative hypothesis:

H1:ρ>0

That is, the correlation between “size of the home” and “selling price” is positive.

Here, the sample size is 105 and the correlation coefficient is 0.371.

The test statistic is as follows:

t=0.371105−21−0.3712=0.371×1030.9286=3.76

Thus, the t-test statistic value is 3.76.

Conclusion:

The value of test statistic is 3.76 and the critical value is 1.659.

Here, t-calculated(=3.76)> t-critical value(=1.659).

By the rejection rule, reject the null hypothesis.

Thus, it can be concluded that there is a positive association between “size of the home” and “selling price”.

Calculation of p-value:

Using excel formula = T.DIST (3.76,103,TRUE)

STAT TECHNIQUES IN BUSI 2370 >CI<, Chapter 13, Problem 62DE , additional homework tip 5

The p-value of the test is 0.000141.

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Students have asked these similar questions

Consider the following set of dependent and independent variables. Use these data to complete parts a and b below. y 48 46 42 42 35 32 30 25 16 x1 78 66 80 52 42 46 30 15 13 x2 22 26 21 20 14 16 9 13 11 a) Construct a 95% confidence interval for the regression coefficient for x1 and interpret its meaning. -The 95% confidence interval for the true population coefficient B1 is ____ to ____. b) Construct a 99% confidence interval for the regression coefficient for x2 and interpret its meaning. -The 99% confidence interval for the true population coefficient B2 is approximately from ___ to ___. I have many of these questions, i need help knowing what steps to take! Thanks!

What is the center of a confidence interval? A)µ B)s C)x̄ D)σ

Given below are seven observations collected in a regression study on two variables, x (independent variable) and y (dependent variable). Copy and paste the numbers in an Excel worksheet and then use Excel's Regression tool to conduct a simple linear regression analysis. Choose 95% confidence level. Answer the following questions: x y 2 12 3 9 6 8 7 7 8 6 7 5 9 2 t statistics is statistically significant at 5% level. Answer Yes or No. Yes No What is the lower bound of the 95% confidence interval for the independent variable x (Keep 2 decimal places) What is the upper bound of the 95% confidence interval for the independent variable x (Keep 2 decimal places)

Answer 2

Question

Compare Compare Correlation is the measure of the degree of the relationship between the variables. In regression, the relationship between the variables to predict one by another is assessed. In correlation there is no cause and effect between the variables, whereas in regression there is a cause and effect between the variables. By using correlation, we cannot predict anything, but regression is a predictive tool. Coefficients are symmetrical in correlation but in regression they are asymmetrical. Correlation is independent of change in origin and scale, but regression is not independent of change in scale.

Chapter 13, Problem 62DE

a.

To determine

Find the regression equation.

Find the selling price of a home with an area of 2,200 square feet.

Construct a 95% confidence interval for all 2,200 square foot homes.

Construct a 95% prediction interval for the selling price of a home with 2,200 square feet.

a.

Expert Solution

Answer to Problem 62DE

The regression equation is y^=64.7931+0.0703x.

The selling price of a home with an area of 2,200 square feet is $219,429.30.

The 95% confidence interval for all 2,200 square foot homes is (210,882.70,227,975.90)

The 95% prediction interval for the selling price of a home with 2,200 square feet is (131,837.60, 307,021.0)

Explanation of Solution

Here, the selling price is the dependent variable and size of the home is the independent variable.

Step-by-step procedure to obtain the ‘regression equation’ using MegaStat software:

In an EXCEL sheet enter the data values of x and y.
Go to Add-Ins > MegaStat > Correlation/Regression > Regression Analysis.
Select input range as ‘Sheet1!$B$2:$B$106’ under Y/Dependent variable.
Select input range ‘Sheet1!$A$2:$A$106’ under X/Independent variables.
Select ‘Type in predictor values’.
Enter 2,200 as ‘predictor values’ and 95% as ‘confidence level’.
Click on OK.

Output obtained using MegaStat software is given below:

STAT TECHNIQUES IN BUSI 2370 >CI<, Chapter 13, Problem 62DE , additional homework tip 1

From the regression output, the regression equation is as follows.

y^=64.7931+0.0703x.

Where y is the selling price and x is the size of the home.

The selling price of a home with an area of 2,200 square feet is $219,429.30.

The 95% confidence interval for all 2,200 square foot homes is (210,882.70,227,975.90)

The 95% prediction interval for the selling price of a home with 2,200 square feet is (131,837.60, 307,021.0)

b.

To determine

Find the regression equation.

Find the selling price of a home with 20 miles from the center of the city.

Construct a 95% confidence interval for homes with 20 miles from the center of the city.

Construct a 95% prediction interval a home with 20 miles from the center of the city.

b.

Expert Solution

Answer to Problem 62DE

The regression equation is y^=270.1670−3.3540(x).

The estimated selling price of a home with 20 miles from the center of the city is $203087.10.

The 95% confidence interval for homes with 20 miles from the center of the city is

(190,267.40,215,906.80)

The 95% prediction interval for homes with 20 miles from the center of the city is

(114,117.8,292,056.5)

Explanation of Solution

Step-by-step procedure to obtain the ‘regression equation’ using MegaStat software:

In an EXCEL sheet enter the data values of x and y.
Go to Add-Ins > MegaStat > Correlation/Regression > Regression Analysis.
Select input range as ‘Sheet1!$C$2:$C$106’ under Y/Dependent variable.
Select input range ‘Sheet1!$B$2:$B$106’ under X/Independent variables.
Select ‘Type in predictor values’.
Enter 20 as ‘predictor values’ and 95% as ‘confidence level’.
Click on OK.

Output obtained using MegaStat software is given below:

STAT TECHNIQUES IN BUSI 2370 >CI<, Chapter 13, Problem 62DE , additional homework tip 2

From the above output, the regression equation is as follows:

y^=270.1670−3.3540(x)

Where y is the selling price of a home and x is the distance from the center of the city.

The estimated selling price of a home with 20 miles from the center of the city is $203087.10.

The 95% confidence interval for homes with 20 miles from the center of the city is (190,267.40,215,906.80)

The 95% prediction interval for a home with 20 miles from the center of the city is

(114,117.8,292,056.5)

c.

To determine

Check whether there is a negative correlation between “distance from the center of the city” and “selling price” using 0.05 significance level.

Check whether there is a positive correlation between the “area of the home” and “selling price” using 0.05 significance level.

Report the p-value of the test and summarize the results.

c.

Expert Solution

Answer to Problem 62DE

There is a negative association between “distance from the center of the city” and “selling price”.

There is a positive association between “selling price” and “area of the home”.

Explanation of Solution

Denote the population correlation as ρ.

The null and alternative hypotheses are stated below:

Null hypothesis:

H0:ρ≥0

That is, the correlation between “distance from the center of the city” and “selling price” is greater than or equal to zero.

Alternative hypothesis:

H1:ρ<0

That is, the correlation between “distance from the center of the city” and “selling price” is less than zero.

Here, the sample size is 105 and the correlation coefficient between “distance from the center of the city” and “selling price” is –0.347.

The test statistic is as follows:

t=−0.347105−21−(−0.347)2=−0.347×1030.9378=−3.75

Thus, the test statistic value is –3.75.

The degrees of freedom is as follows:

df=n−2=105−2=103

The level of significance is 0.05. Therefore, 1−α=0.95.

Critical value:

Step-by-step software procedure to obtain the critical value using EXCEL software:

Open an EXCEL file.
In cell A1, enter the formula “=T.INV (0.95, 103)”.

Output obtained using EXCEL is given as follows:

STAT TECHNIQUES IN BUSI 2370 >CI<, Chapter 13, Problem 62DE , additional homework tip 3

Decision rule:

Reject the null hypothesis H₀, if |t|-calculated> |t|-critical value. Otherwise, fail to reject H₀.

Conclusion:

The value of test statistic is –3.75 and the critical value is 1.659.

Here, |t|-calculated(=3.75)> |t|-critical value(1.659).

By the rejection rule, reject the null hypothesis.

Thus, it can be concluded that there is a negative association between“distance from the center of the city” and “selling price”.

Calculation of p-value:

Using excel formula = T.DIST (–3.75,103,TRUE)

STAT TECHNIQUES IN BUSI 2370 >CI<, Chapter 13, Problem 62DE , additional homework tip 4

The p-value of the test is 0.000.

Check the correlation between independent variables “area of the home” and “selling price” is positive:

The hypotheses are given below:

Null hypothesis:

H0:ρ≤0

That is, the correlation between “size of the home” and “selling price” is less than or equal to zero.

Alternative hypothesis:

H1:ρ>0

That is, the correlation between “size of the home” and “selling price” is positive.

Here, the sample size is 105 and the correlation coefficient is 0.371.

The test statistic is as follows:

t=0.371105−21−0.3712=0.371×1030.9286=3.76

Thus, the t-test statistic value is 3.76.

Conclusion:

The value of test statistic is 3.76 and the critical value is 1.659.

Here, t-calculated(=3.76)> t-critical value(=1.659).

By the rejection rule, reject the null hypothesis.

Thus, it can be concluded that there is a positive association between “size of the home” and “selling price”.

Calculation of p-value:

Using excel formula = T.DIST (3.76,103,TRUE)

STAT TECHNIQUES IN BUSI 2370 >CI<, Chapter 13, Problem 62DE , additional homework tip 5

The p-value of the test is 0.000141.

Want to see more full solutions like this?

Subscribe now to access step-by-step solutions to millions of textbook problems written by subject matter experts!

Answer 3

Question

Compare Compare Correlation is the measure of the degree of the relationship between the variables. In regression, the relationship between the variables to predict one by another is assessed. In correlation there is no cause and effect between the variables, whereas in regression there is a cause and effect between the variables. By using correlation, we cannot predict anything, but regression is a predictive tool. Coefficients are symmetrical in correlation but in regression they are asymmetrical. Correlation is independent of change in origin and scale, but regression is not independent of change in scale.

Chapter 13, Problem 62DE

a.

To determine

Find the regression equation.

Find the selling price of a home with an area of 2,200 square feet.

Construct a 95% confidence interval for all 2,200 square foot homes.

Construct a 95% prediction interval for the selling price of a home with 2,200 square feet.

a.

Expert Solution

Answer to Problem 62DE

The regression equation is y^=64.7931+0.0703x.

The selling price of a home with an area of 2,200 square feet is $219,429.30.

The 95% confidence interval for all 2,200 square foot homes is (210,882.70,227,975.90)

The 95% prediction interval for the selling price of a home with 2,200 square feet is (131,837.60, 307,021.0)

Explanation of Solution

Here, the selling price is the dependent variable and size of the home is the independent variable.

Step-by-step procedure to obtain the ‘regression equation’ using MegaStat software:

In an EXCEL sheet enter the data values of x and y.
Go to Add-Ins > MegaStat > Correlation/Regression > Regression Analysis.
Select input range as ‘Sheet1!$B$2:$B$106’ under Y/Dependent variable.
Select input range ‘Sheet1!$A$2:$A$106’ under X/Independent variables.
Select ‘Type in predictor values’.
Enter 2,200 as ‘predictor values’ and 95% as ‘confidence level’.
Click on OK.

Output obtained using MegaStat software is given below:

STAT TECHNIQUES IN BUSI 2370 >CI<, Chapter 13, Problem 62DE , additional homework tip 1

From the regression output, the regression equation is as follows.

y^=64.7931+0.0703x.

Where y is the selling price and x is the size of the home.

The selling price of a home with an area of 2,200 square feet is $219,429.30.

The 95% confidence interval for all 2,200 square foot homes is (210,882.70,227,975.90)

The 95% prediction interval for the selling price of a home with 2,200 square feet is (131,837.60, 307,021.0)

b.

To determine

Find the regression equation.

Find the selling price of a home with 20 miles from the center of the city.

Construct a 95% confidence interval for homes with 20 miles from the center of the city.

Construct a 95% prediction interval a home with 20 miles from the center of the city.

b.

Expert Solution

Answer to Problem 62DE

The regression equation is y^=270.1670−3.3540(x).

The estimated selling price of a home with 20 miles from the center of the city is $203087.10.

The 95% confidence interval for homes with 20 miles from the center of the city is

(190,267.40,215,906.80)

The 95% prediction interval for homes with 20 miles from the center of the city is

(114,117.8,292,056.5)

Explanation of Solution

Step-by-step procedure to obtain the ‘regression equation’ using MegaStat software:

In an EXCEL sheet enter the data values of x and y.
Go to Add-Ins > MegaStat > Correlation/Regression > Regression Analysis.
Select input range as ‘Sheet1!$C$2:$C$106’ under Y/Dependent variable.
Select input range ‘Sheet1!$B$2:$B$106’ under X/Independent variables.
Select ‘Type in predictor values’.
Enter 20 as ‘predictor values’ and 95% as ‘confidence level’.
Click on OK.

Output obtained using MegaStat software is given below:

STAT TECHNIQUES IN BUSI 2370 >CI<, Chapter 13, Problem 62DE , additional homework tip 2

From the above output, the regression equation is as follows:

y^=270.1670−3.3540(x)

Where y is the selling price of a home and x is the distance from the center of the city.

The estimated selling price of a home with 20 miles from the center of the city is $203087.10.

The 95% confidence interval for homes with 20 miles from the center of the city is (190,267.40,215,906.80)

The 95% prediction interval for a home with 20 miles from the center of the city is

(114,117.8,292,056.5)

c.

To determine

Check whether there is a negative correlation between “distance from the center of the city” and “selling price” using 0.05 significance level.

Check whether there is a positive correlation between the “area of the home” and “selling price” using 0.05 significance level.

Report the p-value of the test and summarize the results.

c.

Expert Solution

Answer to Problem 62DE

There is a negative association between “distance from the center of the city” and “selling price”.

There is a positive association between “selling price” and “area of the home”.

Explanation of Solution

Denote the population correlation as ρ.

The null and alternative hypotheses are stated below:

Null hypothesis:

H0:ρ≥0

That is, the correlation between “distance from the center of the city” and “selling price” is greater than or equal to zero.

Alternative hypothesis:

H1:ρ<0

That is, the correlation between “distance from the center of the city” and “selling price” is less than zero.

Here, the sample size is 105 and the correlation coefficient between “distance from the center of the city” and “selling price” is –0.347.

The test statistic is as follows:

t=−0.347105−21−(−0.347)2=−0.347×1030.9378=−3.75

Thus, the test statistic value is –3.75.

The degrees of freedom is as follows:

df=n−2=105−2=103

The level of significance is 0.05. Therefore, 1−α=0.95.

Critical value:

Step-by-step software procedure to obtain the critical value using EXCEL software:

Open an EXCEL file.
In cell A1, enter the formula “=T.INV (0.95, 103)”.

Output obtained using EXCEL is given as follows:

STAT TECHNIQUES IN BUSI 2370 >CI<, Chapter 13, Problem 62DE , additional homework tip 3

Decision rule:

Reject the null hypothesis H₀, if |t|-calculated> |t|-critical value. Otherwise, fail to reject H₀.

Conclusion:

The value of test statistic is –3.75 and the critical value is 1.659.

Here, |t|-calculated(=3.75)> |t|-critical value(1.659).

By the rejection rule, reject the null hypothesis.

Thus, it can be concluded that there is a negative association between“distance from the center of the city” and “selling price”.

Calculation of p-value:

Using excel formula = T.DIST (–3.75,103,TRUE)

STAT TECHNIQUES IN BUSI 2370 >CI<, Chapter 13, Problem 62DE , additional homework tip 4

The p-value of the test is 0.000.

Check the correlation between independent variables “area of the home” and “selling price” is positive:

The hypotheses are given below:

Null hypothesis:

H0:ρ≤0

That is, the correlation between “size of the home” and “selling price” is less than or equal to zero.

Alternative hypothesis:

H1:ρ>0

That is, the correlation between “size of the home” and “selling price” is positive.

Here, the sample size is 105 and the correlation coefficient is 0.371.

The test statistic is as follows:

t=0.371105−21−0.3712=0.371×1030.9286=3.76

Thus, the t-test statistic value is 3.76.

Conclusion:

The value of test statistic is 3.76 and the critical value is 1.659.

Here, t-calculated(=3.76)> t-critical value(=1.659).

By the rejection rule, reject the null hypothesis.

Thus, it can be concluded that there is a positive association between “size of the home” and “selling price”.

Calculation of p-value:

Using excel formula = T.DIST (3.76,103,TRUE)

STAT TECHNIQUES IN BUSI 2370 >CI<, Chapter 13, Problem 62DE , additional homework tip 5

The p-value of the test is 0.000141.

Want to see more full solutions like this?

Subscribe now to access step-by-step solutions to millions of textbook problems written by subject matter experts!

Answer 4

Question

Compare Compare Correlation is the measure of the degree of the relationship between the variables. In regression, the relationship between the variables to predict one by another is assessed. In correlation there is no cause and effect between the variables, whereas in regression there is a cause and effect between the variables. By using correlation, we cannot predict anything, but regression is a predictive tool. Coefficients are symmetrical in correlation but in regression they are asymmetrical. Correlation is independent of change in origin and scale, but regression is not independent of change in scale.

Chapter 13, Problem 62DE

a.

To determine

Find the regression equation.

Find the selling price of a home with an area of 2,200 square feet.

Construct a 95% confidence interval for all 2,200 square foot homes.

Construct a 95% prediction interval for the selling price of a home with 2,200 square feet.

a.

Expert Solution

Answer to Problem 62DE

The regression equation is y^=64.7931+0.0703x.

The selling price of a home with an area of 2,200 square feet is $219,429.30.

The 95% confidence interval for all 2,200 square foot homes is (210,882.70,227,975.90)

The 95% prediction interval for the selling price of a home with 2,200 square feet is (131,837.60, 307,021.0)

Explanation of Solution

Here, the selling price is the dependent variable and size of the home is the independent variable.

Step-by-step procedure to obtain the ‘regression equation’ using MegaStat software:

In an EXCEL sheet enter the data values of x and y.
Go to Add-Ins > MegaStat > Correlation/Regression > Regression Analysis.
Select input range as ‘Sheet1!$B$2:$B$106’ under Y/Dependent variable.
Select input range ‘Sheet1!$A$2:$A$106’ under X/Independent variables.
Select ‘Type in predictor values’.
Enter 2,200 as ‘predictor values’ and 95% as ‘confidence level’.
Click on OK.

Output obtained using MegaStat software is given below:

STAT TECHNIQUES IN BUSI 2370 >CI<, Chapter 13, Problem 62DE , additional homework tip 1

From the regression output, the regression equation is as follows.

y^=64.7931+0.0703x.

Where y is the selling price and x is the size of the home.

The selling price of a home with an area of 2,200 square feet is $219,429.30.

The 95% confidence interval for all 2,200 square foot homes is (210,882.70,227,975.90)

The 95% prediction interval for the selling price of a home with 2,200 square feet is (131,837.60, 307,021.0)

b.

To determine

Find the regression equation.

Find the selling price of a home with 20 miles from the center of the city.

Construct a 95% confidence interval for homes with 20 miles from the center of the city.

Construct a 95% prediction interval a home with 20 miles from the center of the city.

b.

Expert Solution

Answer to Problem 62DE

The regression equation is y^=270.1670−3.3540(x).

The estimated selling price of a home with 20 miles from the center of the city is $203087.10.

The 95% confidence interval for homes with 20 miles from the center of the city is

(190,267.40,215,906.80)

The 95% prediction interval for homes with 20 miles from the center of the city is

(114,117.8,292,056.5)

Explanation of Solution

Step-by-step procedure to obtain the ‘regression equation’ using MegaStat software:

In an EXCEL sheet enter the data values of x and y.
Go to Add-Ins > MegaStat > Correlation/Regression > Regression Analysis.
Select input range as ‘Sheet1!$C$2:$C$106’ under Y/Dependent variable.
Select input range ‘Sheet1!$B$2:$B$106’ under X/Independent variables.
Select ‘Type in predictor values’.
Enter 20 as ‘predictor values’ and 95% as ‘confidence level’.
Click on OK.

Output obtained using MegaStat software is given below:

STAT TECHNIQUES IN BUSI 2370 >CI<, Chapter 13, Problem 62DE , additional homework tip 2

From the above output, the regression equation is as follows:

y^=270.1670−3.3540(x)

Where y is the selling price of a home and x is the distance from the center of the city.

The estimated selling price of a home with 20 miles from the center of the city is $203087.10.

The 95% confidence interval for homes with 20 miles from the center of the city is (190,267.40,215,906.80)

The 95% prediction interval for a home with 20 miles from the center of the city is

(114,117.8,292,056.5)

c.

To determine

Check whether there is a negative correlation between “distance from the center of the city” and “selling price” using 0.05 significance level.

Check whether there is a positive correlation between the “area of the home” and “selling price” using 0.05 significance level.

Report the p-value of the test and summarize the results.

c.

Expert Solution

Answer to Problem 62DE

There is a negative association between “distance from the center of the city” and “selling price”.

There is a positive association between “selling price” and “area of the home”.

Explanation of Solution

Denote the population correlation as ρ.

The null and alternative hypotheses are stated below:

Null hypothesis:

H0:ρ≥0

That is, the correlation between “distance from the center of the city” and “selling price” is greater than or equal to zero.

Alternative hypothesis:

H1:ρ<0

That is, the correlation between “distance from the center of the city” and “selling price” is less than zero.

Here, the sample size is 105 and the correlation coefficient between “distance from the center of the city” and “selling price” is –0.347.

The test statistic is as follows:

t=−0.347105−21−(−0.347)2=−0.347×1030.9378=−3.75

Thus, the test statistic value is –3.75.

The degrees of freedom is as follows:

df=n−2=105−2=103

The level of significance is 0.05. Therefore, 1−α=0.95.

Critical value:

Step-by-step software procedure to obtain the critical value using EXCEL software:

Open an EXCEL file.
In cell A1, enter the formula “=T.INV (0.95, 103)”.

Output obtained using EXCEL is given as follows:

STAT TECHNIQUES IN BUSI 2370 >CI<, Chapter 13, Problem 62DE , additional homework tip 3

Decision rule:

Reject the null hypothesis H₀, if |t|-calculated> |t|-critical value. Otherwise, fail to reject H₀.

Conclusion:

The value of test statistic is –3.75 and the critical value is 1.659.

Here, |t|-calculated(=3.75)> |t|-critical value(1.659).

By the rejection rule, reject the null hypothesis.

Thus, it can be concluded that there is a negative association between“distance from the center of the city” and “selling price”.

Calculation of p-value:

Using excel formula = T.DIST (–3.75,103,TRUE)

STAT TECHNIQUES IN BUSI 2370 >CI<, Chapter 13, Problem 62DE , additional homework tip 4

The p-value of the test is 0.000.

Check the correlation between independent variables “area of the home” and “selling price” is positive:

The hypotheses are given below:

Null hypothesis:

H0:ρ≤0

That is, the correlation between “size of the home” and “selling price” is less than or equal to zero.

Alternative hypothesis:

H1:ρ>0

That is, the correlation between “size of the home” and “selling price” is positive.

Here, the sample size is 105 and the correlation coefficient is 0.371.

The test statistic is as follows:

t=0.371105−21−0.3712=0.371×1030.9286=3.76

Thus, the t-test statistic value is 3.76.

Conclusion:

The value of test statistic is 3.76 and the critical value is 1.659.

Here, t-calculated(=3.76)> t-critical value(=1.659).

By the rejection rule, reject the null hypothesis.

Thus, it can be concluded that there is a positive association between “size of the home” and “selling price”.

Calculation of p-value:

Using excel formula = T.DIST (3.76,103,TRUE)

STAT TECHNIQUES IN BUSI 2370 >CI<, Chapter 13, Problem 62DE , additional homework tip 5

The p-value of the test is 0.000141.

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Answer 5

Chapter 13, Problem 62DE

a.

To determine

Find the regression equation.

Find the selling price of a home with an area of 2,200 square feet.

Construct a 95% confidence interval for all 2,200 square foot homes.

Construct a 95% prediction interval for the selling price of a home with 2,200 square feet.

a.

Expert Solution

Answer to Problem 62DE

The regression equation is y^=64.7931+0.0703x.

The selling price of a home with an area of 2,200 square feet is $219,429.30.

The 95% confidence interval for all 2,200 square foot homes is (210,882.70,227,975.90)

The 95% prediction interval for the selling price of a home with 2,200 square feet is (131,837.60, 307,021.0)

Explanation of Solution

Here, the selling price is the dependent variable and size of the home is the independent variable.

Step-by-step procedure to obtain the ‘regression equation’ using MegaStat software:

In an EXCEL sheet enter the data values of x and y.
Go to Add-Ins > MegaStat > Correlation/Regression > Regression Analysis.
Select input range as ‘Sheet1!$B$2:$B$106’ under Y/Dependent variable.
Select input range ‘Sheet1!$A$2:$A$106’ under X/Independent variables.
Select ‘Type in predictor values’.
Enter 2,200 as ‘predictor values’ and 95% as ‘confidence level’.
Click on OK.

Output obtained using MegaStat software is given below:

STAT TECHNIQUES IN BUSI 2370 >CI<, Chapter 13, Problem 62DE , additional homework tip 1

From the regression output, the regression equation is as follows.

y^=64.7931+0.0703x.

Where y is the selling price and x is the size of the home.

The selling price of a home with an area of 2,200 square feet is $219,429.30.

The 95% confidence interval for all 2,200 square foot homes is (210,882.70,227,975.90)

The 95% prediction interval for the selling price of a home with 2,200 square feet is (131,837.60, 307,021.0)

b.

To determine

Find the regression equation.

Find the selling price of a home with 20 miles from the center of the city.

Construct a 95% confidence interval for homes with 20 miles from the center of the city.

Construct a 95% prediction interval a home with 20 miles from the center of the city.

b.

Expert Solution

Answer to Problem 62DE

The regression equation is y^=270.1670−3.3540(x).

The estimated selling price of a home with 20 miles from the center of the city is $203087.10.

The 95% confidence interval for homes with 20 miles from the center of the city is

(190,267.40,215,906.80)

The 95% prediction interval for homes with 20 miles from the center of the city is

(114,117.8,292,056.5)

Explanation of Solution

Step-by-step procedure to obtain the ‘regression equation’ using MegaStat software:

In an EXCEL sheet enter the data values of x and y.
Go to Add-Ins > MegaStat > Correlation/Regression > Regression Analysis.
Select input range as ‘Sheet1!$C$2:$C$106’ under Y/Dependent variable.
Select input range ‘Sheet1!$B$2:$B$106’ under X/Independent variables.
Select ‘Type in predictor values’.
Enter 20 as ‘predictor values’ and 95% as ‘confidence level’.
Click on OK.

Output obtained using MegaStat software is given below:

STAT TECHNIQUES IN BUSI 2370 >CI<, Chapter 13, Problem 62DE , additional homework tip 2

From the above output, the regression equation is as follows:

y^=270.1670−3.3540(x)

Where y is the selling price of a home and x is the distance from the center of the city.

The estimated selling price of a home with 20 miles from the center of the city is $203087.10.

The 95% confidence interval for homes with 20 miles from the center of the city is (190,267.40,215,906.80)

The 95% prediction interval for a home with 20 miles from the center of the city is

(114,117.8,292,056.5)

c.

To determine

Check whether there is a negative correlation between “distance from the center of the city” and “selling price” using 0.05 significance level.

Check whether there is a positive correlation between the “area of the home” and “selling price” using 0.05 significance level.

Report the p-value of the test and summarize the results.

c.

Expert Solution

Answer to Problem 62DE

There is a negative association between “distance from the center of the city” and “selling price”.

There is a positive association between “selling price” and “area of the home”.

Explanation of Solution

Denote the population correlation as ρ.

The null and alternative hypotheses are stated below:

Null hypothesis:

H0:ρ≥0

That is, the correlation between “distance from the center of the city” and “selling price” is greater than or equal to zero.

Alternative hypothesis:

H1:ρ<0

That is, the correlation between “distance from the center of the city” and “selling price” is less than zero.

Here, the sample size is 105 and the correlation coefficient between “distance from the center of the city” and “selling price” is –0.347.

The test statistic is as follows:

t=−0.347105−21−(−0.347)2=−0.347×1030.9378=−3.75

Thus, the test statistic value is –3.75.

The degrees of freedom is as follows:

df=n−2=105−2=103

The level of significance is 0.05. Therefore, 1−α=0.95.

Critical value:

Step-by-step software procedure to obtain the critical value using EXCEL software:

Open an EXCEL file.
In cell A1, enter the formula “=T.INV (0.95, 103)”.

Output obtained using EXCEL is given as follows:

STAT TECHNIQUES IN BUSI 2370 >CI<, Chapter 13, Problem 62DE , additional homework tip 3

Decision rule:

Reject the null hypothesis H₀, if |t|-calculated> |t|-critical value. Otherwise, fail to reject H₀.

Conclusion:

The value of test statistic is –3.75 and the critical value is 1.659.

Here, |t|-calculated(=3.75)> |t|-critical value(1.659).

By the rejection rule, reject the null hypothesis.

Thus, it can be concluded that there is a negative association between“distance from the center of the city” and “selling price”.

Calculation of p-value:

Using excel formula = T.DIST (–3.75,103,TRUE)

STAT TECHNIQUES IN BUSI 2370 >CI<, Chapter 13, Problem 62DE , additional homework tip 4

The p-value of the test is 0.000.

Check the correlation between independent variables “area of the home” and “selling price” is positive:

The hypotheses are given below:

Null hypothesis:

H0:ρ≤0

That is, the correlation between “size of the home” and “selling price” is less than or equal to zero.

Alternative hypothesis:

H1:ρ>0

That is, the correlation between “size of the home” and “selling price” is positive.

Here, the sample size is 105 and the correlation coefficient is 0.371.

The test statistic is as follows:

t=0.371105−21−0.3712=0.371×1030.9286=3.76

Thus, the t-test statistic value is 3.76.

Conclusion:

The value of test statistic is 3.76 and the critical value is 1.659.

Here, t-calculated(=3.76)> t-critical value(=1.659).

By the rejection rule, reject the null hypothesis.

Thus, it can be concluded that there is a positive association between “size of the home” and “selling price”.

Calculation of p-value:

Using excel formula = T.DIST (3.76,103,TRUE)

STAT TECHNIQUES IN BUSI 2370 >CI<, Chapter 13, Problem 62DE , additional homework tip 5

The p-value of the test is 0.000141.

Answer 6

Chapter 13, Problem 62DE

a.

To determine

Find the regression equation.

Find the selling price of a home with an area of 2,200 square feet.

Construct a 95% confidence interval for all 2,200 square foot homes.

Construct a 95% prediction interval for the selling price of a home with 2,200 square feet.

a.

Expert Solution

Answer to Problem 62DE

The regression equation is y^=64.7931+0.0703x.

The selling price of a home with an area of 2,200 square feet is $219,429.30.

The 95% confidence interval for all 2,200 square foot homes is (210,882.70,227,975.90)

The 95% prediction interval for the selling price of a home with 2,200 square feet is (131,837.60, 307,021.0)

Explanation of Solution

Here, the selling price is the dependent variable and size of the home is the independent variable.

Step-by-step procedure to obtain the ‘regression equation’ using MegaStat software:

In an EXCEL sheet enter the data values of x and y.
Go to Add-Ins > MegaStat > Correlation/Regression > Regression Analysis.
Select input range as ‘Sheet1!$B$2:$B$106’ under Y/Dependent variable.
Select input range ‘Sheet1!$A$2:$A$106’ under X/Independent variables.
Select ‘Type in predictor values’.
Enter 2,200 as ‘predictor values’ and 95% as ‘confidence level’.
Click on OK.

Output obtained using MegaStat software is given below:

STAT TECHNIQUES IN BUSI 2370 >CI<, Chapter 13, Problem 62DE , additional homework tip 1

From the regression output, the regression equation is as follows.

y^=64.7931+0.0703x.

Where y is the selling price and x is the size of the home.

The selling price of a home with an area of 2,200 square feet is $219,429.30.

The 95% confidence interval for all 2,200 square foot homes is (210,882.70,227,975.90)

The 95% prediction interval for the selling price of a home with 2,200 square feet is (131,837.60, 307,021.0)

Answer 7

Chapter 13, Problem 62DE

a.

To determine

Find the regression equation.

Find the selling price of a home with an area of 2,200 square feet.

Construct a 95% confidence interval for all 2,200 square foot homes.

Construct a 95% prediction interval for the selling price of a home with 2,200 square feet.

Answer 8

a.

Expert Solution

Answer to Problem 62DE

The regression equation is y^=64.7931+0.0703x.

The selling price of a home with an area of 2,200 square feet is $219,429.30.

The 95% confidence interval for all 2,200 square foot homes is (210,882.70,227,975.90)

The 95% prediction interval for the selling price of a home with 2,200 square feet is (131,837.60, 307,021.0)

Answer 9

a.

Expert Solution

Answer 10

a.

Expert Solution

Answer 11

Expert Solution

Answer 12

Explanation of Solution

Here, the selling price is the dependent variable and size of the home is the independent variable.

Step-by-step procedure to obtain the ‘regression equation’ using MegaStat software:

In an EXCEL sheet enter the data values of x and y.
Go to Add-Ins > MegaStat > Correlation/Regression > Regression Analysis.
Select input range as ‘Sheet1!$B$2:$B$106’ under Y/Dependent variable.
Select input range ‘Sheet1!$A$2:$A$106’ under X/Independent variables.
Select ‘Type in predictor values’.
Enter 2,200 as ‘predictor values’ and 95% as ‘confidence level’.
Click on OK.

Output obtained using MegaStat software is given below:

STAT TECHNIQUES IN BUSI 2370 >CI<, Chapter 13, Problem 62DE , additional homework tip 1

From the regression output, the regression equation is as follows.

y^=64.7931+0.0703x.

Where y is the selling price and x is the size of the home.

The selling price of a home with an area of 2,200 square feet is $219,429.30.

The 95% confidence interval for all 2,200 square foot homes is (210,882.70,227,975.90)

The 95% prediction interval for the selling price of a home with 2,200 square feet is (131,837.60, 307,021.0)

Answer 13

b.

To determine

Find the regression equation.

Find the selling price of a home with 20 miles from the center of the city.

Construct a 95% confidence interval for homes with 20 miles from the center of the city.

Construct a 95% prediction interval a home with 20 miles from the center of the city.

b.

Expert Solution

Answer to Problem 62DE

The regression equation is y^=270.1670−3.3540(x).

The estimated selling price of a home with 20 miles from the center of the city is $203087.10.

The 95% confidence interval for homes with 20 miles from the center of the city is

(190,267.40,215,906.80)

The 95% prediction interval for homes with 20 miles from the center of the city is

(114,117.8,292,056.5)

Explanation of Solution

Step-by-step procedure to obtain the ‘regression equation’ using MegaStat software:

In an EXCEL sheet enter the data values of x and y.
Go to Add-Ins > MegaStat > Correlation/Regression > Regression Analysis.
Select input range as ‘Sheet1!$C$2:$C$106’ under Y/Dependent variable.
Select input range ‘Sheet1!$B$2:$B$106’ under X/Independent variables.
Select ‘Type in predictor values’.
Enter 20 as ‘predictor values’ and 95% as ‘confidence level’.
Click on OK.

Output obtained using MegaStat software is given below:

STAT TECHNIQUES IN BUSI 2370 >CI<, Chapter 13, Problem 62DE , additional homework tip 2

From the above output, the regression equation is as follows:

y^=270.1670−3.3540(x)

Where y is the selling price of a home and x is the distance from the center of the city.

The estimated selling price of a home with 20 miles from the center of the city is $203087.10.

The 95% confidence interval for homes with 20 miles from the center of the city is (190,267.40,215,906.80)

The 95% prediction interval for a home with 20 miles from the center of the city is

(114,117.8,292,056.5)

Answer 14

b.

To determine

Find the regression equation.

Find the selling price of a home with 20 miles from the center of the city.

Construct a 95% confidence interval for homes with 20 miles from the center of the city.

Construct a 95% prediction interval a home with 20 miles from the center of the city.

Answer 15

b.

Expert Solution

Answer to Problem 62DE

The regression equation is y^=270.1670−3.3540(x).

The estimated selling price of a home with 20 miles from the center of the city is $203087.10.

The 95% confidence interval for homes with 20 miles from the center of the city is

(190,267.40,215,906.80)

The 95% prediction interval for homes with 20 miles from the center of the city is

(114,117.8,292,056.5)

Answer 16

b.

Expert Solution

Answer 17

b.

Expert Solution

Answer 18

Expert Solution

Answer 19

Explanation of Solution

Step-by-step procedure to obtain the ‘regression equation’ using MegaStat software:

In an EXCEL sheet enter the data values of x and y.
Go to Add-Ins > MegaStat > Correlation/Regression > Regression Analysis.
Select input range as ‘Sheet1!$C$2:$C$106’ under Y/Dependent variable.
Select input range ‘Sheet1!$B$2:$B$106’ under X/Independent variables.
Select ‘Type in predictor values’.
Enter 20 as ‘predictor values’ and 95% as ‘confidence level’.
Click on OK.

Output obtained using MegaStat software is given below:

STAT TECHNIQUES IN BUSI 2370 >CI<, Chapter 13, Problem 62DE , additional homework tip 2

From the above output, the regression equation is as follows:

y^=270.1670−3.3540(x)

Where y is the selling price of a home and x is the distance from the center of the city.

The estimated selling price of a home with 20 miles from the center of the city is $203087.10.

The 95% confidence interval for homes with 20 miles from the center of the city is (190,267.40,215,906.80)

The 95% prediction interval for a home with 20 miles from the center of the city is

(114,117.8,292,056.5)

Answer 20

c.

To determine

Check whether there is a negative correlation between “distance from the center of the city” and “selling price” using 0.05 significance level.

Check whether there is a positive correlation between the “area of the home” and “selling price” using 0.05 significance level.

Report the p-value of the test and summarize the results.

c.

Expert Solution

Answer to Problem 62DE

There is a negative association between “distance from the center of the city” and “selling price”.

There is a positive association between “selling price” and “area of the home”.

Explanation of Solution

Denote the population correlation as ρ.

The null and alternative hypotheses are stated below:

Null hypothesis:

H0:ρ≥0

That is, the correlation between “distance from the center of the city” and “selling price” is greater than or equal to zero.

Alternative hypothesis:

H1:ρ<0

That is, the correlation between “distance from the center of the city” and “selling price” is less than zero.

Here, the sample size is 105 and the correlation coefficient between “distance from the center of the city” and “selling price” is –0.347.

The test statistic is as follows:

t=−0.347105−21−(−0.347)2=−0.347×1030.9378=−3.75

Thus, the test statistic value is –3.75.

The degrees of freedom is as follows:

df=n−2=105−2=103

The level of significance is 0.05. Therefore, 1−α=0.95.

Critical value:

Step-by-step software procedure to obtain the critical value using EXCEL software:

Open an EXCEL file.
In cell A1, enter the formula “=T.INV (0.95, 103)”.

Output obtained using EXCEL is given as follows:

STAT TECHNIQUES IN BUSI 2370 >CI<, Chapter 13, Problem 62DE , additional homework tip 3

Decision rule:

Reject the null hypothesis H₀, if |t|-calculated> |t|-critical value. Otherwise, fail to reject H₀.

Conclusion:

The value of test statistic is –3.75 and the critical value is 1.659.

Here, |t|-calculated(=3.75)> |t|-critical value(1.659).

By the rejection rule, reject the null hypothesis.

Thus, it can be concluded that there is a negative association between“distance from the center of the city” and “selling price”.

Calculation of p-value:

Using excel formula = T.DIST (–3.75,103,TRUE)

STAT TECHNIQUES IN BUSI 2370 >CI<, Chapter 13, Problem 62DE , additional homework tip 4

The p-value of the test is 0.000.

Check the correlation between independent variables “area of the home” and “selling price” is positive:

The hypotheses are given below:

Null hypothesis:

H0:ρ≤0

That is, the correlation between “size of the home” and “selling price” is less than or equal to zero.

Alternative hypothesis:

H1:ρ>0

That is, the correlation between “size of the home” and “selling price” is positive.

Here, the sample size is 105 and the correlation coefficient is 0.371.

The test statistic is as follows:

t=0.371105−21−0.3712=0.371×1030.9286=3.76

Thus, the t-test statistic value is 3.76.

Conclusion:

The value of test statistic is 3.76 and the critical value is 1.659.

Here, t-calculated(=3.76)> t-critical value(=1.659).

By the rejection rule, reject the null hypothesis.

Thus, it can be concluded that there is a positive association between “size of the home” and “selling price”.

Calculation of p-value:

Using excel formula = T.DIST (3.76,103,TRUE)

STAT TECHNIQUES IN BUSI 2370 >CI<, Chapter 13, Problem 62DE , additional homework tip 5

The p-value of the test is 0.000141.

Answer 21

c.

To determine

Check whether there is a negative correlation between “distance from the center of the city” and “selling price” using 0.05 significance level.

Check whether there is a positive correlation between the “area of the home” and “selling price” using 0.05 significance level.

Report the p-value of the test and summarize the results.

Answer 22

c.

Expert Solution

Answer to Problem 62DE

There is a negative association between “distance from the center of the city” and “selling price”.

There is a positive association between “selling price” and “area of the home”.

Answer 23

c.

Expert Solution

Answer 24

c.

Expert Solution

Answer 25

Expert Solution

Answer 26

Explanation of Solution

Denote the population correlation as ρ.

The null and alternative hypotheses are stated below:

Null hypothesis:

H0:ρ≥0

That is, the correlation between “distance from the center of the city” and “selling price” is greater than or equal to zero.

Alternative hypothesis:

H1:ρ<0

That is, the correlation between “distance from the center of the city” and “selling price” is less than zero.

Here, the sample size is 105 and the correlation coefficient between “distance from the center of the city” and “selling price” is –0.347.

The test statistic is as follows:

t=−0.347105−21−(−0.347)2=−0.347×1030.9378=−3.75

Thus, the test statistic value is –3.75.

The degrees of freedom is as follows:

df=n−2=105−2=103

The level of significance is 0.05. Therefore, 1−α=0.95.

Critical value:

Step-by-step software procedure to obtain the critical value using EXCEL software:

Open an EXCEL file.
In cell A1, enter the formula “=T.INV (0.95, 103)”.

Output obtained using EXCEL is given as follows:

STAT TECHNIQUES IN BUSI 2370 >CI<, Chapter 13, Problem 62DE , additional homework tip 3

Decision rule:

Reject the null hypothesis H₀, if |t|-calculated> |t|-critical value. Otherwise, fail to reject H₀.

Conclusion:

The value of test statistic is –3.75 and the critical value is 1.659.

Here, |t|-calculated(=3.75)> |t|-critical value(1.659).

By the rejection rule, reject the null hypothesis.

Thus, it can be concluded that there is a negative association between“distance from the center of the city” and “selling price”.

Calculation of p-value:

Using excel formula = T.DIST (–3.75,103,TRUE)

STAT TECHNIQUES IN BUSI 2370 >CI<, Chapter 13, Problem 62DE , additional homework tip 4

The p-value of the test is 0.000.

Check the correlation between independent variables “area of the home” and “selling price” is positive:

The hypotheses are given below:

Null hypothesis:

H0:ρ≤0

That is, the correlation between “size of the home” and “selling price” is less than or equal to zero.

Alternative hypothesis:

H1:ρ>0

That is, the correlation between “size of the home” and “selling price” is positive.

Here, the sample size is 105 and the correlation coefficient is 0.371.

The test statistic is as follows:

t=0.371105−21−0.3712=0.371×1030.9286=3.76

Thus, the t-test statistic value is 3.76.

Conclusion:

The value of test statistic is 3.76 and the critical value is 1.659.

Here, t-calculated(=3.76)> t-critical value(=1.659).

By the rejection rule, reject the null hypothesis.

Thus, it can be concluded that there is a positive association between “size of the home” and “selling price”.

Calculation of p-value:

Using excel formula = T.DIST (3.76,103,TRUE)

STAT TECHNIQUES IN BUSI 2370 >CI<, Chapter 13, Problem 62DE , additional homework tip 5

The p-value of the test is 0.000141.

Answer 27

Ch. 13 - Prob. 1SR Ch. 13 - Prob. 1E Ch. 13 - Prob. 2E Ch. 13 - Bi-lo Appliance Super-Store has outlets in several...Ch. 13 - Prob. 4E Ch. 13 - Prob. 5E Ch. 13 - The owner of Maumee Ford-Volvo wants to study the...Ch. 13 - Prob. 2SR Ch. 13 - Prob. 7E Ch. 13 - Prob. 8E

Find the regression equation. Find the selling price of a home with an area of 2,200 square feet. Construct a 95% confidence interval for all 2,200 square foot homes. Construct a 95% prediction interval for the selling price of a home with 2,200 square feet.

Concept explainers

Videos

Find the regression equation.

Find the selling price of a home with an area of 2,200 square feet.

Construct a 95% confidence interval for all 2,200 square foot homes.

Construct a 95% prediction interval for the selling price of a home with 2,200 square feet.

Answer to Problem 62DE

Explanation of Solution

Find the regression equation.

Find the selling price of a home with 20 miles from the center of the city.

Construct a 95% confidence interval for homes with 20 miles from the center of the city.

Construct a 95% prediction interval a home with 20 miles from the center of the city.

Answer to Problem 62DE

Explanation of Solution

Answer to Problem 62DE

Explanation of Solution

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Chapter 13 Solutions

Find the regression equation. Find the selling price of a home with an area of 2,200 square feet. Construct a 95% confidence interval for all 2,200 square foot homes. Construct a 95% prediction interval for the selling price of a home with 2,200 square feet.

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Find the regression equation. Find the selling price of a home with an area of 2,200 square feet. Construct a 95% confidence interval for all 2,200 square foot homes. Construct a 95% prediction interval for the selling price of a home with 2,200 square feet.

Answer to Problem 62DE

Explanation of Solution

Find the regression equation. Find the selling price of a home with 20 miles from the center of the city. Construct a 95% confidence interval for homes with 20 miles from the center of the city. Construct a 95% prediction interval a home with 20 miles from the center of the city.

Answer to Problem 62DE

Explanation of Solution

Answer to Problem 62DE

Explanation of Solution

Want to see more full solutions like this?

Chapter 13 Solutions

Find the regression equation.

Find the selling price of a home with an area of 2,200 square feet.

Construct a 95% confidence interval for all 2,200 square foot homes.

Construct a 95% prediction interval for the selling price of a home with 2,200 square feet.

Find the regression equation.

Find the selling price of a home with 20 miles from the center of the city.

Construct a 95% confidence interval for homes with 20 miles from the center of the city.

Construct a 95% prediction interval a home with 20 miles from the center of the city.