Residuals. For the following data, (a) Compute the least squaresline for Y in terms of X. (b) Use your regression equation to computea predicted value of Y when Xproblem has a residual. The residual belonging to the i-th data pointis defined to be yiresidual corresponding to the data point r = 3, y = 5. If the residualsfor each data point are summed the result is 0. The sum of the squaresof the residuals is denoted SSE. The statistic SSE is minimized by theregression line, which is why the regression line is also called the "least5. Each data point in a regression(bo + b1ri) or, more briefly, Yi – Îi- (c) Find thesquares line."0 1 2 3 4Y14 7 9 5 5

Given the data of response variable y and predictor variable x. We have to find the least square…

Answered: Residuals. For the following data, (a)…

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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In a pretest, data were obtained from 20 respondents on purchase intention for restaurant that provide food delivery service on a 7-point scale where 1 = weak intention and 7 = strong intention. The respondents are to rate the restaurant on quality of food, portion size, value for money, and quality of service, using 7-point scales where 1 = poor and 7 = excellent. The resulting data as follow. a "purchase intention.sav (Dataset1) - 18M SPSS Statistics Data Editor Ele Edt yew Rata Iransform Analyze Graphs ybides Estensions Window Help Name Туре Width Decimals Label Values Missing Columns Measure Role Align Right ID Numeric ID None None Unknown SInput Purchase_Intention Numeric Quality Portion Value For_Money Numeric Purchase_Intent. (1.00, weak. None (1.00, poor). None (1.00, poor). None Value_For_Money (1.00, poor). None (1.00. poor). None Right SInput SInput Unknown 3 Numeric Quality Portion Right Unknown Numeric 2 Right Unknown Sinput Right | Right Right 2 8 Unknown SInput Senice…
The table shows the numbers of new-vehicle sales (in thousands) in the United States for Company A and Company B for 10 years. The equation of the regression line is y = 0.991x + 1,222.81. Complete parts (a) and (b) below. New-vehicle sales (Company A), x New-vehicle sales (Company B), y 4,149 3,923 3,566 3,400 3,266 3,076 2,868 2,485 1,952 2,066 4,912 4,871 4,827 4,721 4,672 4,474 4,684 3,822 2,956 2,754 (a) Find the coefficient of determination and interpret the result. r² = r2 = 0.821 (Round to three decimal places as needed.) How can the coefficient of determination be interpreted? The coefficient of determination is the fraction of the variation in new-vehicle sales for Company B that can be 2 explained by the variation in new-vehicle sales for Company A and is represented by The remaining fraction of the variation, 1-2, is unexplained and is due to other factors or to sampling error. s (b) Find the standard error of estimates and interpret the result. Se O (Round to three decimal…
The table shows the average weekly wages (in dollars) for state government employees and federal government employees for 8 years. The equation of the regression line is y=1.410x−17.174. Complete parts (a) and(b) below.
# The table contains the state population and the number of licensed drivers in the state (both in millions) for the states with population under 1 million in 2014. The regression model for this data is y 0.7x where x is the state population (in millions) and y is the number of State licensed drivers (in millions) in the state. (A) Draw a scatter plot of the data and a graph of the model on the same axes. Choose the correct graph below OC Diverse) 07 Se pun CHANG The estimated population of state Jin 2014 is (Type a whole number Round to the nearest thousand as needed) 0.5 (8) If the population of state H in 2014 was about 1.6 million, use the model to estimate the number of licensed drivers in state H in 2014 The estimated number of licensed drivers in state H in 2014 is (Type a whole number. Round to the nearest thousand as needed) (C) If the number of licensed drivers in state J in 2014 was about 1,043.000, use the model to estimate the population of state Jin 2014 AOCDEFO А С OD…
Data on tuition and mid-career salary are collected from a number of universities and colleges. The result of the data collection is the linear regression model ŷ=0.93x + 167 where x = annual tuition and y = average mid-career salary of graduates, both in thousands of dollars. 1. Which quantity is the independent variable? O average mid-career salary of graduates annual tuition OF 2. According to this model, what is the average salary for a graduate of a college or university where the annual tuition is $30,000? $ 3. What is the slope of this regression model?
The annual expenditure for cell phones varies by the age of an individual. The average annual expenditure E(a) (in $) for individuals of age a (in years) is given below:a: 20, 30, 40, 50, 60, 70E(a): 502, 658, 649, 627, 476, 2131. Use quadratic regression to find the model that best represents the data.2. At what age is the yearly expenditure for cell phones the greatest? Round the answer to the nearest year. YOU MUST SHOW THE WORK FOR THIS PART!
Solve b
Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The number of hours 6 students spent for a test and their scores on that test are shown below. Hours spent studying, x Test score, y (a) x= 2 hours (c) x = 14 hours (b) x= 4.5 hours (d) x = 2.5 hours 40 45 52 47 65 69 Find the regression equation. ý =]x+ (O (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.)
The owner of Showtime Movie Theaters, Inc., would like to predict weekly gross revenue as a function of advertising expenditures. Historical data for a sample of eight weeks follow. Weekly Gross Revenue ($1,000s) 96 90 ŷ = 95 92 95 94 94 94 Television Newspaper Advertising Advertising ($1,000s) ($1,000s) 5.0 2.0 4.0 2.5 3.0 3.5 2.5 3.0 1.5 2.0 1.5 2.5 3.3 2.3 4.2 2.5 (a) Develop an estimated regression equation with the amount of television advertising as the independent variable. (Round your numerical values to two decimal places. Let X₁ amount of television advertising in $1,000s and y represent the weekly gross revenue in $1,000s.) ŷ = represent the (b) Develop an estimated regression equation with both television advertising and newspaper advertising as the independent variables. (Round your numerical values to two decimal places. Let x₁ represent the amount of television advertising in $1,000s, x₂ represent the amount of newspaper advertising in $1,000s, and y represent the weekly…
A statistical program is recommended. The owner of Showtime Movie Theaters, Inc., would like to predict weekly gross revenue as a function of advertising expenditures. Historical data for a sample of eight weeks follow. Weekly Television Gross Newspaper Advertising Advertising ($1,000s) ($1,000s) Revenue ($1,000s) 96 5.0 1.5 90 2.0 2.0 95 4.0 1.5 92 2.5 2.5 95 3.0 3.3 94 3.5 2.3 94 2.5 4.2 94 3.0 2.5 1 (a) Develop an estimated regression equation with the amount of television advertising as the independent variable. (Round your numerical values to two decimal places. Let x₁ represent the amount of television advertising in $1,000s and y represent the weekly gross revenue in $1,000s.) y = 88.64 + 1.60x1 X (b) Develop an estimated regression equation with both television advertising and newspaper advertising as the independent variables. (Round your numerical values to two decimal places. Let x₁ represent the amount of television advertising in $1,000s, x₂ represent the amount of…
The table shows the amounts of crude oil (in thousands of barrels per day) produced by a certain country and the amounts of crude oil (in thousands of barrels per day) imported by the same country for seven years. The equation of the regression line is y = - 1.269x + 16,635.60. Complete parts (a) and (b) below. Produced, x Imported, y 5,718 5,612 5,409 5,228 5,128 5,006 O 9,106 9,631 10,000 10,140 10,133 10,059 5,759 9,318 (a) Find the coefficient of determination and interpret the result. (Round to three decimal places as needed.)
Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The number of hours 6 students spent for a test and their scores on that test are shown below. Hours spent studying, x Test score, y (a) x = 2 hours (c) x = 14 hours (b) x = 4.5 hours (d) x = 1.5 hours 2 3 4 4 6 38 45 51 48 64 67 Find the regression equation. ŷ =x+ (O (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.) Choose the correct graph below. A. ОВ. OD. 80- 80- Hours studying Hours studying Hours studying Hours studying (a) Predict the value of y for x = 2. Choose the correct answer below. O A. 44.5 О В. 58.8 OC. 41.7 O D. not meaningful (b) Predict the value of y for x = 4.5. Choose the correct answer below. O A. 58.8 О В. 41.7 OC.…

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