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Problem 5- Simple Linear Regression The following data represent the number of flash drives sold per...
The following data represent the number of flash drives sold per day at a local computer...
The following data represent the number of flash drives sold per day at a local computer shop and their prices. Price (x) Units Sold (y) 34 36 32 35 30 38 40 4 Refer to Case 2 data use Excel, Data Analysis, Regression tools and develop a least-squares regression line and explain what the slope of the line indicates y-esimated 29.7857 0.7286x The slope indicates that as the price goes up by $1, the number of units sold goes up...
The following data represent the number of flash drives sold per day at a local computer...
The following data represent the number of flash drives sold per day at a local computer shop and their prices. Price (x) Units Sold (y) 34 36 32 35 30 38 40 4 Refer to Case 2 data use Excel, Data Analysis, Regression tools and develop a least-squares regression line and explain what the slope of the line indicates y-esimated 29.7857 0.7286x The slope indicates that as the price goes up by $1, the number of units sold goes up...
Problem 6 Simple Linear Regression To the Internal Revenue Service, the reasonableness of total itemized deductions...
Problem 6 Simple Linear Regression To the Internal Revenue Service, the reasonableness of total itemized deductions depends on the taxpayer's adjusted gross income. Large deductions, which include charity and medical deductions, are more reasonable for taxpayers with large adjusted gross incomes. If a taxpayer claims larger than average itemized deductions for a given level of income, the chances of an IRS audit are increased. Data (in thousands of dollars) on adjusted gross income and the average or reasonable amount of...
Simple Linear regression 1. A researcher uses a simple linear regression to measure the relationship between...
Simple Linear regression
1. A researcher uses a simple linear regression to measure the relationship between the monthly salary (Salary measured in dollars) of data scientists and the number of years since being awarded a Master degree (Master Degree). A random sample of 80 observations was collected for the analysis. A researcher used the econometric model which has the following specification Salary,-β0 + β, Master-Degree, + εί, where i = 1, , 80 The (incomplete) Excel output of equation (1)...
Multiple Regression Analysis This information is taken from 80 homes recently sold along the Gulf of...
Multiple Regression Analysis This information is taken from 80 homes recently sold along the Gulf of Mexico coast.Analyze the data to discover which of the variable have a statistically significant influence on the sales price. A. Write out the equation for the model you develop B, Interpret the equation as a model and the meaning of the information for each variable in your "best" model C.Interpret the confidence intervals for each of the statistically significant variables Use the data provided...
HW # 5 Linear Regression: Use Data Analysis in Excel to conduct the Regression Analysis to...
HW # 5 Linear Regression: Use Data Analysis in Excel to conduct the Regression Analysis to reproduce the excel out put below (Note: First enter the data in the next page in an Excel spreadsheet) Home Sale Price: The table below provides the Excel output of a regression analysis of the relationship between Home sale price(Y) measured in thousand dollars and Square feet area (x): SUMMARY OUTPUT Dependent: Home Price ($1000) Regression Statistics Multiple R 0.691 R Square 0.478 Adjusted...
(d) Write down the fitted simple linear regression model (equation) and discuss its merits using the following outp...
(d) Write down the fitted simple linear regression model (equation) and discuss its merits using the following output. Consider the intercept, slope, overall goodness of model etc. when commenting. (Note that, in Excel, the time variable begins at Year 1900, i.e. 01/01/1900, 12am). [4 marks] Intercept X Variable 1 Coefficients -164070 5.736757 Standard Error t Stat P-value 28361.13278 -5.785021448 1.64E-06 0.749106082 7.65813654 6.68E-09 Lower 95% Upper 95% -221706.5175 -106433.01 4.214389946 7.2591234
What does the error term in the simple linear regression model account for? What are the...
What does the error term in the simple linear regression model account for? What are the parameters of the simple linear model When all the points fall on the regression line, what is the value of the correlation coefficient? Part of an Excel output relating 15 observations of X (independent variable) and Y (dependent variable) is shown below. Provide the values for a-e shown in the table below. (See section 15.5) Summary Output ANOVA df SS MS F Significance F...
#1 In simple linear regression, r is the: a) coefficient of determination. b) mean square error. ...
#1 In simple linear regression, r is the: a) coefficient of determination. b) mean square error. c) correlation coefficient. d) squared residual. #2 In regression analysis, with the model in the form y = β0 + β1x + ε, x is the a) estimated regression equation. b) y-intercept. c) slope. d) independent variable. #3 A regression analysis between sales (y in $1,000s) and advertising (x in dollars) resulted in the following equation. ŷ = 40,000 + 3x The above equation...
Part (c) (2 points) Interpret the estimated value of the coefficient on the “GPA” variable,...
Part (c)
(2
points)
Interpret the estimated value of the coefficient on the “GPA”
variable, i.e., explain what the number means in this
regression.
The coefficient for GPA is -6.3746. It means that for every
unit it increases there is a decrease of -6.3746 units in
time.
Part
(e)
(2 points)
Is the estimate of the coefficient on the “GPA” variable
statistically significant? Please answer “yes” or “no,”
then explain how we can tell.
The estimate is statistically significant;...
The following data represent the number of flash drives sold per day at a local computer shop and their prices. Price (x) Units Sold (y) 34 36 32 35 30 38 40 4 Refer to Case 2 data use Excel, Data Analysis, Regression tools and develop a least-squares regression line and explain what the slope of the line indicates y-esimated 29.7857 0.7286x The slope indicates that as the price goes up by $1, the number of units sold goes up...
The following data represent the number of flash drives sold per day at a local computer shop and their prices. Price (x) Units Sold (y) 34 36 32 35 30 38 40 4 Refer to Case 2 data use Excel, Data Analysis, Regression tools and develop a least-squares regression line and explain what the slope of the line indicates y-esimated 29.7857 0.7286x The slope indicates that as the price goes up by $1, the number of units sold goes up...
Problem 6 Simple Linear Regression To the Internal Revenue Service, the reasonableness of total itemized deductions depends on the taxpayer's adjusted gross income. Large deductions, which include charity and medical deductions, are more reasonable for taxpayers with large adjusted gross incomes. If a taxpayer claims larger than average itemized deductions for a given level of income, the chances of an IRS audit are increased. Data (in thousands of dollars) on adjusted gross income and the average or reasonable amount of...
Simple Linear regression
1. A researcher uses a simple linear regression to measure the relationship between the monthly salary (Salary measured in dollars) of data scientists and the number of years since being awarded a Master degree (Master Degree). A random sample of 80 observations was collected for the analysis. A researcher used the econometric model which has the following specification Salary,-β0 + β, Master-Degree, + εί, where i = 1, , 80 The (incomplete) Excel output of equation (1)...
(d) Write down the fitted simple linear regression model (equation) and discuss its merits using the following output. Consider the intercept, slope, overall goodness of model etc. when commenting. (Note that, in Excel, the time variable begins at Year 1900, i.e. 01/01/1900, 12am). [4 marks] Intercept X Variable 1 Coefficients -164070 5.736757 Standard Error t Stat P-value 28361.13278 -5.785021448 1.64E-06 0.749106082 7.65813654 6.68E-09 Lower 95% Upper 95% -221706.5175 -106433.01 4.214389946 7.2591234
Part (c)
(2
points)
Interpret the estimated value of the coefficient on the “GPA”
variable, i.e., explain what the number means in this
regression.
The coefficient for GPA is -6.3746. It means that for every
unit it increases there is a decrease of -6.3746 units in
time.
Part
(e)
(2 points)
Is the estimate of the coefficient on the “GPA” variable
statistically significant? Please answer “yes” or “no,”
then explain how we can tell.
The estimate is statistically significant;...
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