2. A study on the factor that determine sales (y in millions of dollars) for a big grocery store chain. Thefactors considered are advertising expenditures (x) in thousands of dollars), and number ofsalespeople (x2). The following is part of the results:ANOVASourceRegressiondfSSMS22956.064Error15736.012a. What has been the sample size for this regression analysis?b. At a = 05, test to determine if the model is significant. That is, determine if there exists asignificant relationship between the independent variables and the dependent variable.c. Determine the multiple coefficient of determination R².d. Determine the adjusted multiple coefficient of determination (adjusted R?).

Answered: Image /qna-images/answer/4d8d3c67-15c6-4c19-8733-8ea77b06b947.jpg

Answered: 2. A study on the factor that determine…

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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Shoe size and height, in inches, of 15 randomly selected high school students are compared. Which significance test should be used to see if height and shoe size have a linear relationship? Assume all test conditions are met. O t-test for slope of regression line OTwo-sample z-test O Two-sample t-test O Two-proportion z-test O One-proportion z-test
A regional retailer would like to determine if the variation in average monthly store sales can, in part, be explained by the size of the store measured in square feet. A random sample of 21 stores was selected and the store size and average monthly sales were computed. Complete parts a through c. Use a significance level of 0.10 where needed. 1 Click the icon to view the data table between the store size and average monthly sales. Compute the simple linear regression model using the sample data to determine whether variation in average monthly sales can be explained by store size. What is the linear regression model based on the sample data? y= +( )x(Type integers or decimals rounded to two decimal places as needed.) Interpret the slope coefficient. Select the correct choice below and fill in the answer box to complete your choice. (Type an integer or decimal rounded to two decimal places as needed.) For each additional square foot of store size,…
please use the chart attatched. a. Determine the explanatory and response variables from the table above. b. What is the equation of the regression line corresponding to values above? c. What is the coefficient of determination? What can we say about the regression line using the coefficient of determination?
3. A regression of infant mortality rates (annual deaths per thousand births) on median annual household income (data entered in thousands of dollars) is performed on data collected from 34 counties. The results are summarized below: Intercept 18.46 Slope -0.14 Sum of Mean squares df square Regression Residual 1.8 Total 3.4 (a) Fill in the blanks in the ANOVA table. (b) What is the predicted infant mortality rate in a county where the median annual household income is $40,000? (c) In words, what is the meaning of the coefficient -0.14? Do not simply say thát this is the slope or the regression coefficient; indicate what it means and how it can be interpreted.
**Answer the questions with the data on picture, please. a) Determine the sample correlation coefficient rxy b) Determine the sample regression equation: y= b0+b1x c) Compute the coefficient of determination. d) What is the predicted explanatory value if the response value is 8?
Rrr
Suppose you are analyzing a dataset of 319 datapoints for using in a multiple regression model. Using 7 different predictor variables, you conduct an ANOVA test for your model, yielding a SSE of 2443 and SSR of 1162. Using this information, what is the R² of your analysis? Note: 1- Do NOT express your result as a percent. Your result should be a number between 0 and 1. 2- Only round your final answer. Round your final answer to two decimal places.
Please answer ASAP, thank you !
You were given a dataset that includes 100 datapoints for expenses in Canadian dollars and waste in kilo grams. Based on the data you were able to calculate the following: The variance of the expenses = 78515151.52 The variance of the waste amount 14602.38, The R squared = 0.372460641, Intercept = cS 34046.3765, Total waste amount = 54420 kg ion Then the slope of the regression line is (approximately) O a 44,75124 O b. 54.420 Oc 5840 Od. 34.04637
. A professor at the University of Alabama was interested in evaluating the relationship between family support and delinquency. Using data collected on 4545 families, the researcher used regression to analyze the relationship. The results are presented below. Variables Entered/Removeda Model Variables Entered Variables Removed Method 1 Family supportb . Enter a. Dependent Variable: Delinquency b. All requested variables entered. Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .249a .062 .062 1.59168 a. Predictors: (Constant), Family support ANOVAa Model Sum of Squares df Mean Square F Sig. 1 Regression 759.204 1 759.204 299.671 <.001b Residual 11479.107 4531 2.533 Total 12238.311 4532 a. Dependent Variable: Delinquency b. Predictors: (Constant), Family support…
The weight and systolic blood pressure of 26 randomly selected males in the age group 25 – 30 are shown below. Assume that weight and blood pressure (BP) are jointly normally distributed. a. Find a regression line relating systolic blood pressure to weight. b. Estimate the correlation coefﬁcient. c. Test the significance of the regression coefficient (Use the Variance Analysis Table) d. Work in two ways using manuals and statistical applications (analyze the results of both)
Suppose a doctor measures the height, x, and head circumference, y, of 11 children and obtains the data below. The correlation coefficient is 0.883 and the least squares regression line is y = 0.134x + 13.693. Complete parts (a) and (b) below. Height, x Head Circumference, y 17.4 27.75 25.25 26 25.25 27.25 26.75 26 27.25 27 27.25 26.75 17.1 17.3 17.0 17.4 17.2 17.2 17.3 17.3 17.4 17.3 ..... (a) Compute the coefficient of determination, R?. R? % (Round to one decimal place as needed.) (b) Interpret the coefficient of determination. Approximately % of the variation in is explained by the least-squares gression model. (Round to one decimal place as needed.)

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