The first three parts a,b,c have already been answered. Please help with the last blank of part c and part d. Thank you A regression model relating , number of salespersons at a branch office, to y, annual sales at the office (in thousands of dollars) provided the followingregression output. Where total = = 40.O Icon KeyQI4RF10.38V%5TANOVAInterceptNumber ofSalespersonsa. Write the estimated regression equation (to whole number).ŷ=88 +58 Tb. Compute the F statistic and test the significance of the relationship at a 0.05 level of significance. (to 2 decimals)119.85t Statp-value is less than 0.01# , we rejectHo: B₁=d. Predict the annual sales at the Memphis branch office. This branch employs 14 salespersons.$thousand (to whole number)GRegressionResidualTotalF-valuep-value is less than 0.01# , we rejectHoc. Compute the t statistic and test the significance of the relationship at a 0.05 level of significance. (to 2 decimals)6BCoefficientsYHdfMacBook Pro&88.058.0.7NSS6,761.88,905.8U*00MS FStandard Error11.3385.5898JDM(9Significance FKt Stat P-value<%O-C<HLP-T+{1[S2111?IC1

The question is about regression Given : Coefficient of intercept ( b0 ) = 88 Coefficient of no. of…

Answered: A regression model relating , number of…

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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A researcher examined the relationship between the annual tax amount paid by the construction company owners and the total expense items spent for the construction with regression analysis and calculated the regression line estimation as Y=6+2X. According to this; Write the interpretations of the cutoff and regression parameters, respectively, in your OWN SENTENCES in a statistically appropriate way over the tax amount and expenses.
Suppose the athletic director at a university would like to develop a regression model to predict the point differential for games played by the men's basketball team. A point differential is the difference between the final points scored by two competing teams. A positive differential is a win, and a negative differential is a loss. For a random sample of games, the point differential was calculated, along with the number of assists, rebounds, turnovers, and personal fouls. Use the data in the accompanying table attached below to complete parts a through e below. Assume a = 0.05. a) Using technology, construct a regression model using all three independent variables. y = __ + (_)x1 + (_)x2 + (_)x3 + (_)x4 b) Test the significance of each independent variable using a= 0.10. c) interpret the p-value for each independent variable. d) Construxt a 90% confidence interval for the regression coefficients for each independent variable and interpret the meaning. e) Using the results from…
A group of scientists are interested in finding out whether the days of rainfall during the dry season could predict the magnitude of butterfly migration in the local area during wet season. Every year for twenty years, they count the total days of rainfall during the dry season preceding the migration and measure the number of butterflies migrating in the following wet season. Which type of statistical test should they use to analyze their data? (pearson's r correlation OR, simple regression equation)
Find the simple regression line y=α+βx for the pairs of points belonging to the independent and dependent variables (xi,yi) , respectively. Also, interpret the result by calculating the Pearson correlation coefficient.
suppose that you want to conduct a study on the relationship between women's shoe sizes and their height, and you have collected samples of female undergraduates at your university. The mean height of women in your sample is 64 inches, with a standard deviation of 2 inches. The mean shoe size is 8, with a standard deviation of 1. The correlation between the shoe size and height in your sample is .05. What is the least squares estimate of the slope parameter in your regression model?
The number of pounds of steam used per month by a chemical plant is thought to be related to the average ambient temperature (in F) for that month. The past year’s usage and temperatures are in the following table: Assuming that a simple linear regression model is appropriate, fit the regression model relating stem usage (y) to the average temperature (x). What is the estimate of Sigma2? What is the estimate of expected stem usage when the average temperature is 55 F? What change in mean stem usage is expected when the monthly average temperature changes by 1 F? Suppose that the monthly average temperature is 47 F. Calculate the fitted value of y and the corresponding residual. Test for significance of regression using α=0.01 (Use ANOVA). Calculate the r2 of the model. Find a 99% CI for B1 .
The following table gives the ages of female students in school and the corresponding Body Mass index (BMI) of 8 randomly selected students.(α=0.05) Age24223032211925 BMI27283029282726 Determine whether ages and BMI are significantly related.Determine the coefficient of linear determination and Intepret.Set up a linear regression equation to predict body mass index from age of students.Predict the body mass index of student who has the age of 26 years.
A 10-year study conducted by the American Heart Association provided data on how age, blood pressure, and smoking relate to the risk of strokes (Dataset "Stroke"). Risk is interpreted as the probability (times 100) that a person will have a stroke over the next 10-year period. For the smoker variable, 1 indicates a smoker and 0 indicates a nonsmoker. a. Develop an estimated regression equation that can be used to predict the risk of stroke given the age and blood-pressure level. b. Consider adding two independent variables to the model developed in part (a), one for the interaction between age and blood-pressure level and the other for whether the person is a smoker. Develop an estimated regression equation using these four independent variables. c. At a 0.05 level of significance, test to see whether the addition of the interaction term and the smoker variable contributes significantly to the estimated regression equation developed in part (a). d. Refer to the model developed in part…
What is the sample regression equation (round to 2 decimal places)? y = + Education + Experience + Age What is the hourly wage for a 30-year-old worker with 4 years of higher education and 3 years of experience (round to 2 decimal places)? Are any independent variables insignificant?
Calculate the equation of the regression line and calculate the correlation coefficient
After performing a statistical regression on a set of data the value of the correlation coefficient r was -0.2041. What does that imply about the data?
A multiple regression model has been fit to a data set with p predictor variables, and the adjusted R-squared value is 0.75. What can we conclude about the model fit and the predictor variables in the model?

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