Mark Gershon, owner of a musical instrument distributorship, thinks that demand for guitars maybe related to the number of television appearances by the popular group Maroon 5 during theprevious month. Gershon has collected the data shown in the following table:Maroon 5 TV AppearancesDemand for Guitars424 8 5 7 758 6 10 6This exercise contains only parts b, c, and d.b) Using the least-squares regression method, the equation for forecasting is (round yourresponses to four decimal places):Y = -0.9774 + 1.225 xc) The estimate for guitar sales if Maroon 5 performed on TV 9 times = 10.05 sales (round yourresponse to two decimal places).d) The correlation coefficient (r) for this model =(round your response to four decimal places).

From the information, given that

Answered: Mark Gershon, owner of a musical…

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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The following is the data for Patient Days (the cost driver) and Maintenance Costs for a local hospital: Month Patient Days (Cost driver) Maintenance Costs January 3,300 $4,450 February 4,050 $4,750 March 3,000 $4,200 April 3, 750 $ 4,600 May 4,150 $5,050 June 4,500 $5,400 July 2,600 $4,400 Using regression analysis to analyze the hospital's cost structure, the estimated fixed maintenance cost for the hospital is: $5,468 $0.793 $2,734 $0.541
Grade Prediction. The Statistics Department at a large university would like to predict the final grades of students in its introductory statistics course. a. If the final grade is measured as a percentage from 0% to 100%, suggest five predictor variables that might be useful in predicting final grade. b. Write the multiple linear regression model for the conditional mean of the response variable, final grade.
A chemical engineer is investigating the effect of process operating temperature on product yield. The study results in the following data: Temperature Yield 100 57.71 110 63.17 120 76.30 130 73.30 140 89.07 150 91.17 160 170 114.11 106.33 180 190 114.38 124.07 You can use Minitab to answer the following questions. However, you should be able to calculate the slope and intercept of the least squares regression model by hand, which requires only the mear and standard deviations of X and Y, and the correlation coefficient (here r = 0.9751). 1. what is the mean temperature? 155 150 130 145 Submit Answer Tries 0/2
Name Her Age His Age Barack and Michelle Obama 45 47 George W. and Laura Bush 54 54 Bill and Hillary Clinton 45 46 Ronald and Nancy Reagan 55 64 Gerald and Betty Ford 59 69 Lyndon and Lady Bird Johnson 56 61 John and Jacqueline Kennedy 31 43 Dwight and Mamie Eisenhower 50 55 (c) Remove the outlier and compute the least-squares regression line for predicting the president's age from first lady's age. Round the slope and y -intercept values to at least four decimal places. Regression line equation: =y
PROBLEM : The amount spent on medical expenses per day is correlated with other health factors for 5 adult males. A study came up with the following table: (attached picture) 1. Create the regression equation for the problem. 2. Which of the following factors has a significant effect on medical expenses? Show all necessary computations and solutions. Follow the hypothesis testing procedure.
In multiple regression analysis, a problem that is not found in simple linear regressions can be caused by the correlation among the independent variables. This problem is called… …multicollaboration …multicollinearity …multicultural …correlation collateral damage
3. Setup: The data set "Healthy Breakfast" contains, among other variables, the Consumer Reports ratings of 77 cereals and the number of grams of sugar contained in each serving. (Data source: Free publication available in many grocery stores. Data set available through the Statlib Data and Story.) Considering "Sugars" as the explanatory variable and "Rating" as the response variable generated the following regression line: Rating = 59.3-2.40 - Sugars. and the ANOVA table Source Regression Error Total SS df MS 8654.7 1 8654.7 102.35 6342.1 75 84.6 14996.8 76 F Questions: (a) Write down the simple linear regression model and its model assumption. (b) State the null and alternative hypotheses for the model. Based on the ANOVA table, draw conclusion based on the p-value for the test. (c) Obtain Srz and the standard error se (3₁) to construct the 95% confidence interval for $₁.
How strongly do physical characteristics of sisters and brothers correlate? Here are data on the heights (in inches) of 12 adult pairs: Brother 71 68 66 67 70 71 70 73 72 65 66 70 Sister 69 64 65 63 65 62 65 64 66 59 62 64 (a) Use your calculator or software to find the correlation and the equation of the least-squares line for predicting sister’s height from brother’s height. Make a scatterplot of the data and add the regression line to your plot. Damien is 70 inches tall. Predict the height of his sister Tonya. Based on the scatterplot and the correlation r, do you expect your prediction to be very accurate? Why?
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Section 10.2 Question #11 The data show the number of viewers for television stars with certain salaries. Find the regression equation, letting salary be the independent (x) variable. Find the best predicted number of viewers for a television star with a salary of $11million. Is the result close to the actual number of viewers, 3.3 million? Use a significance level of 0.05. Salary (millions of $) 108 15 2 15 3 8 4 14 Viewers (millions) 9.1 9.3 10.9 1.3 4.8 4.8 3.2 1.8 View the critical values of the Pearson correlation coefficient r. Critical values of the pearson correlation coefficient r n α=0.05 α=0.01 NOTE: To test H0: ρ=0 against H1: ρ≠0,reject H0if the absolute value of r is greater than the critical value in the table. 4 0.950 0.990 5 0.878 0.959 6 0.811 0.917 7 0.754 0.875 8 0.707 0.834 9 0.666 0.798 10 0.632 0.765 11 0.602 0.735…
Café Michigan's manager, Gary Stark, suspects that demand for mocha latte coffees depends on the price being charged. Based on historical observations, Gary has gathered the following data, which show the numbers of these coffees sold over six different price values: Price $2.70 $3.40 $1.90 $4.10 $3.00 $4.00 Using simple linear regression, and given that the price per cup is $1.80, the forecasted demand for mocha latte coffees will be cups (enter your response rounded to one decimal place). Number Sold 765 510 980 245 320 480
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