(1) Write out the regression equation (2) What is the sample size used in this investigation? (3) Determine the values of *, ** and ***, ****
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(1) Write out the regression equation
(2) What is the sample size used in this investigation?
(3) Determine the values of *, ** and ***, ****
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- What is regression analysis? Describe the process of performing regression analysis on a graphing utility.Assume that you want to predict Company Performance based on the linear effects of Trust and Commitment that exist among a company’s employees c) If you want to test whether there is a linear effect of Commitment and a curvilinear effect of Trust on Company Performance—such that Company Performance increases up to a certain level of Trust, after which Company Performance diminishes with increasing Trust levels—how would your regression equation look like? Further, explain your answer in your own words. Provide at least two sentences of explanation, in addition to giving the regression equation.A business statistics professor would like to develop a regression model to predict the final exam scores for students based on their current GPAs, the number of hours they studied for the exam, the number of times they were absent during the semester, and their genders. The data for these variables are given in the accompanying table at the bottom of this page. a) Using Excel, construct a regression model using all of the independent variables. Create the dummy variable Gen, which equals 1 for a male and 0 for a female student ( this assignment is arbitrary) complete the regression equation for the model below, where y= Score, x1= GPA, x2= Hours, x3= Absenses, and x4= Gen. y= (__) + (__)x1 + (__)x2 + (__)x3 + (__)x4 b) Test the significance of the overall regression model using a= 0.10. c) interpret the meaning of the regression coefficient for the dummy variable. d) using the p-values, identify which independent variables are significant with a= 0.10. e) construct a regression…
- The data point height=175 cm, height =80 cm was misrecorded as height=145 cm, height =80 cm. If we use the simple linear regression and do not correct the mistake, what is the impact of this point on the model?When should a regression model not be used to make a prediction?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…
- An automotive sales manager wishes to examine the relationship between age (years) and sales price ($) for used automobiles of a certain brand. The accompanying table contains data for a sample of a certain make and model that were listed for sale at a car shopping website. b. Fit a quadratic regression model to predict price and state the quadratic regression equation.A study in the univeristy of massachusetts amherst published in the may 2007 journal of marriage and family found that married women do about one fewer hour of housework a week for every $7500 they earn as a full time workers outside of the home, regardless of their husband's income A) what would be the numerical value of the slope coefficient in the regression model that predicts womens housework hours from their income? what does the sign of the slope (positive or negative) tell us about the relationship between these variables B) Suppose Lynette's salary is $30,000 greater than Gabriells. what would you predict the difference in hours of housework they each do.A medical researcher wants to determine how a new medication affects blood pressure. An amount of medication of 145 mg is found to result in a blood pressure of 128.42 mm Hg. What is the predicted blood pressure? Where is the observed value in relation to the regression line? The equation of the regression line is �^=140+(−0.0667)�. Where is the observed value in relation to the regression line? An amount of medication of 178 mg is found to result in a blood pressure of 128.13 mm Hg. What is the predicted blood pressure? Where is the observed value in relation to the regression line? An amount of medication of 200 mg is found to result in a blood pressure of 129.15 mm Hg. What is the predicted blood pressure? The options for the drop down boxes are below, above or on the regression line.
- when a regression is used as a method of predicting dependent variables from one or more independent variables. How are the independent variables different from each other yet related to the dependent variable?Develop an estimated multiple regression equation that relates risk of a stroke to a person's age, systolic blood pressure and whether the person is a smoker. x1=persons age x2systrolic blood pressure x3=whether person is a smoker or non smokerCan the regression equation reasonably be used to make predictions