1. In an effort to demostrate the importance of class attendance, a statistics instructortakes daily attendance one semester throughout a Stat 289 class. A random sampleof the students is selected. Their number of absences and corresponding final gradesare listed in the following table:StudentStudentStudentStudentStudentStudent1346.ExAbsences0.2146.Grade859370514250yPart of a linear regression analysis has been completed with the following sums alreadycalculated:Σα21.= 127, Ey = 391, Ey² = 27639,Ery = 1120.(a) Calculate the numbers s, 8y, Sy, and the correlation coefficient r for this data.(b) Find the equation y = a + bx of the linear regression (best fit) line. (Show thecalculation.)(c) What is the predicted grade for a student who is absent 4 times in the semester?

List of formulae : Sample standard deviation of variable x : sx = ∑x2-∑x2nn-1 Sample standard…

Answered: 1. In an effort to demonstrate the…

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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Two measures of a baseball player's effectiveness as a hitter are the number of hits he makes in a season and thenumber of times he "bats in" a run (knows as "Runs Batted In" or RBIs). Can we predict a batter's RBIs from hisMajor League Baseball batters in 2017.hits? Below is numerical and graphical output from a computer regression of RBIs on Hits for 12 randomly selected Major League Baseball batters in 2017. Assume that the conditions for inference have been satisfied.(a) Do these data provide convincing evidence that there is a linear relationship between RBIs and Flits for MajorLeague Baseball batters in 2017? (b) Construct a 95% confidence interval for the slope of the population regression line for predicting RBIs from Hits.
The U.S. Department of Energy’s Fuel Economy Guide provides fuel efficiency data for cars and trucks. The following regression output was obtained for a sample of 45 cars. The variable of interest is highway miles per gallon (Hwy MPG). The independent variables used in the analysis are as follows: The class of the vehicle: Compact, Midsize or Large. Midsize = 1 if the car is a midsize, 0 otherwise. Similarly, Large = 1 if it is a large car, 0 otherwise. Displcement: The engine displacement (size) in liters Premium: Equals 1 if premium fuel is used, 0 if regular fuel is used Cylinders: Number of cylinders Regression Statistics Multiple R 0.90 R Square Adjusted R Square 0.79 Standard Error 1.78 Observations 45 ANOVA df SS MS F Significance F…
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Can movie rental revenue be predicted? A movie studio wishes to determine the relationship between the revenue from rental of comedies on streaming services and the revenue generated from the theatrical release of such movies. The studio has the following bivariate data from a sample of fifteen comedies released over the past five years. These data give the revenue x from theatrical release (in millions of dollars) and the revenue y from streaming service rentals (in millions of dollars) for each of the fifteen movies. Also shown are the scatter plot and the least-squares regression line for the data. The equation for this line is ŷ=3.38+0.15x. Theater revenue, x (in millions of dollars) Rental revenue, y (in millions of dollars) 21.0 5.5 60.9 10.0 61.0 16.0 27.5 3.1 36.7 12.7 30.6 5.7 14.8 2.0 49.6 15.7 13.1 10.2 25.9 8.9 44.1 6.5 66.9 9.5 27.5 11.8 24.9 7.9 6.9 1.5 Send data to calculator Send data to Excel Rental revenue (in millions of dollars) 18- 16+ x 14 12 10+ x 50 60 70…
The following table shows the starting salary and profile of a sample of 10 2 p employees in a certain call center agency. Run a multiple regression analysis with starting salary as the dependent variable (pesos) and GPA, years of experience and civil service ratings as the independent variables. Use .05 level of significance.What is the computed R square of the resulting multiple linear regression and its interpretation? * Civil Years of Starting salary GPA service experience ratings 79.5 15000 80.1 15000 81.2 78.0 15500 81.3 79.0 16000 82.4 80.0 16200 83.4 85.0 17500 87.9 89.9 89.1 18000 90.3 16,300 84.2 17000 87.0 17900 88.1 84.1 89.0 89.2 R squared = 0.8053; This means that 80.53% of the total variation in the starting salary can be explained by its linear relationship with GPA, years of experience and civil service ratings. R squared = 0.9651; This means that 96.51% of the total variation in the starting salary can be explained by its linear relationship with GPA, years of…
A company wishes to estimate a regression line for the relationship between sales and advertising. а. To arrive at its decision regarding the best model to use, the company has calculated the following three correlation coefficients. i. ii. The sales in any month depend on that month's advertising with r = 0.28 The sales in any month depend on 50% of the previous month's advertising and 50% of that month's advertising with r= 0.68 The sales in any month depend on the previous month's advertising with r = 0.92 iii. Interpret each of the above correlation coefficients and state which of the suggested models you would choose as the basis for predicting sales. Justify your answer.
A movie studio wishes to determine the relationship between the revenue from rental of comedies on streaming services and the revenue generated from the theatrical release of such movies. The studio has the following bivariate data from a sample of fifteen comedies released over the past five years. These data give the revenue x from theatrical release (in millions of dollars) and the revenue y from streaming service rentals (in millions of dollars) for each of the fifteen movies. Also shown are the scatter plot and the least-squares regression line for the data. The equation for this line is y = 3.58 +0.15x. Theater revenue, x (in millions of dollars) 26.4 36.7 43.5 31.6 60.4 14.8 21.3 49.3 7.7 24.8 27.8 12.9 60.6 26.4 66.4 Send data to calculator V Rental revenue, y (in millions of dollars) 8.1 12.4 6.8 5.1 15.4 2.6 5.8 16.5 2.2 9.1 3.3 9.8 10.8 11.7 9.6 Based on the studio's data and the regression line, complete the following. Rental revenue in millions of dollars) 0 X 10 X 20…
Please give answers of b&c
Consider the following data on y = number of songs stored on an MP3 player and x = number of months the user has owned the MP3 player for a sample of 15 owners of MP3 players. x y 22 485 34 748 2 81 28 581 5 117 32 728 23 445 10 128 4 61 26 476 1 35 8 121 13 266 9 126 5 141 What is the equation of the estimated regression line? (Round your numerical values to four decimal places.) y = Is the simple linear regression model useful for describing the relationship between x and y? Test the relevant hypotheses using a significance level of 0.05. Calculate the test statistic. (Round your answer to two decimal places.) t = find the P-value for this test? (Round your answer to four decimal places.) P-value=
10
Consider the following computer output from a multiple regression analysis relating the cost of car insurance to the variables: number of car accidents, driver's credit score, and safety rating of the car. Intercept Car Accidents (In last 3 years) Credit Score Safety Rating Coefficients 1186 213.48 Coefficients - 130.46 294.11 Standard Error Does the sign of the coefficient for the variable safety rating make sense? 123.87 21.89 14.26 356.37 t Stat P-value 9.575 0.0000 9.752 0.0000 -9.149 0.0000 0.825 0.4128
The following data has mid term marks and end term marks of 9 students. Maximum marksfor both mid term marks as well as end term marks is 100. Calculate regression line betweenmid term marks (independent) and end term marks (Dependent) using below dataset. Givedetailed explanation with solution.Student Roll No. 1 2 3 4 5 6 7 8 9Mid TermMarks 67 59 73 63 89 78 64 28 89End TermMarks 55 42 80 83 76 67 63 33 58

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