Following is a portion of the regression output for an application relating maintenance expense (dollars per month) to usage (hours per week) for a particular brand of computer terminal. Excel File: data14-41.xlsx ANOVA df SS MS Significance F Regression 1 1575.76 Residual 8. 349.14 Total 1924.90 Coefficients Standard Error t Stat P-value Intercept 6.1092 0.9361 Usage 0.8951 0.149 If your answer is zero, enter "0". a. Write the estimated regression equation (to 4 decimals). b. Use a t test to determine whether monthly maintenance expense is related to usage at the 0.05 level of significance (to 2 decimals). Use Table 2 of Append В. t = p-value = - Select your answer v the null hypothesis. Monthly maintenance expense - Select your answer - v related to usage. c. Did the estimated regression equation provide a good fit? Explain. Hint: If r is greater than 0.50, the estimated regression equation provides a good fit. - Select your answer - because the value of re is - Select your answer - v than 0.50.
Following is a portion of the regression output for an application relating maintenance expense (dollars per month) to usage (hours per week) for a particular brand of computer terminal. Excel File: data14-41.xlsx ANOVA df SS MS Significance F Regression 1 1575.76 Residual 8. 349.14 Total 1924.90 Coefficients Standard Error t Stat P-value Intercept 6.1092 0.9361 Usage 0.8951 0.149 If your answer is zero, enter "0". a. Write the estimated regression equation (to 4 decimals). b. Use a t test to determine whether monthly maintenance expense is related to usage at the 0.05 level of significance (to 2 decimals). Use Table 2 of Append В. t = p-value = - Select your answer v the null hypothesis. Monthly maintenance expense - Select your answer - v related to usage. c. Did the estimated regression equation provide a good fit? Explain. Hint: If r is greater than 0.50, the estimated regression equation provides a good fit. - Select your answer - because the value of re is - Select your answer - v than 0.50.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
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Transcribed Image Text:Following is a portion of the regression output for an application relating maintenance expense (dollars per month) to usage (hours per week) for a particular
brand of computer terminal.
Excel File: data14-41.xlsx
ANOVA
df
SS
MS
F
Significance F
Regression
1575.76
Residual
8
349.14
Total
1924.90
Coefficients Standard Error
t Stat
P-value
Intercept
6.1092
0.9361
Usage
0.8951
0.149
If your answer is zero, enter "0".
a. Write the estimated regression equation (to 4 decimals).
ŷ =
b. Use a t test to determine whether monthly maintenance expense is related to usage at the 0.05 level of significance (to 2 decimals). Use Table 2 of Appendix
В.
t =
p-value
- Select your answer v the null hypothesis. Monthly maintenance expense
Select your answer -
related to usage.
c. Did the estimated regression equation provide a good fit? Explain. Hint: If r is greater than 0.50, the estimated regression equation provides a good fit.
- Select your answer - V
because the value of r2 is
- Select your answer - v than 0.50.
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