Q5. The random error for the sample regression model, denoted by e, is equal to the:A) predicted value of y minus the estimated value of yB) estimated value of y minus the predicted value of yC) actual value of y minus the predicted value of yD) actual value of y minus the actual value of x

The objective is to determine the error in simple linear regression. The simple linear regression of…

Answered: Q5. The random error for the sample…

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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f (x, y) y g (x) DIRE 135 1 0.05 0.05 0.00 0.10 K NX 0.05 0.10 0.20 0.35 3 0.10 0.35 0.10 0.55 h (y) 0.20 0.50 0.30 1
The Kak Ramah company supplies vegetables to shop as wholesales. The demand for the vegetables depends on the price per kilograms (kg). the data are shown in the following table. Price per 20 22 24 26 28 30 32 kg (RM) Demand 700 685 630 580 515 490 450 (kg) a)By using the linear regression line, calculate the number of sales if the price per kg is RM25 b) Calculate the Pearson correlation value and interpret
3. Can SAT scores predict college performance? Let x be a variable that represents SAT score of a computer science major, and let y be a variable that represents a student’s GPA upon graduation. A random sample of n =15 computer science majors provided their SAT scores and GPAs: x 1232 1070 1086 1287 1130 1048 1121 1095 1135 1208 1333 1160 1186 1243 1261 y 3.52 2.91 2.4 3.47 3.47 2.37 2.4 2.24 3.02 3.32 3.59 2.54 3.19 3.71 3.58 The scatter diagram for the SAT score and GPA is given below: (a) Find the sample correlation coefficient r. Truncate to two decimal places. What does the value tell you about the data? (b) Find the equation of the least squares line . Truncate to four decimal places. What does the slope mean? (c) Find the value of the coefficient of determination . Truncate to two decimal places. What does this number mean? (d) What is the predicted GPA if a computer science major got a…
A corporation owns several companies. The planner for the corporation believes the amount spent on advertising can predict the total sales of the company. She gathers the following sales and advertising information from several of the companies for 2015 (in millions). Advertising 12.5 3.5 21.4 10.5 12.2 8.9 7.6 12.4 18.7 Sales 148 26 120 100 157 58 67 123 196 What is the simple regression line that can best predict the sales from the advertising expenditures using these data? Oŷ 84.15x 45.81 Oŷ = 7.52x + 20.57 ỹ = 3.45x – 45.12 Oŷ = 7.31x + 19.86
The personnel director of a large hospital is interested in determining the relationship (if any) between an employee’s age and the number of sick days the employee takes per year. The director randomly selects ten employees and records their age and the number of sick days which they took in the previous year. Employee 1 2 3 4 5 6 7 8 9 10 Age 30 50 40 55 30 28 60 25 30 45 Sick Days 7 4 3 2 9 10 0 8 5 2 Copy Data The estimated regression line and the standard error are given. Sick Days=14.310162−0.2369(Age) se=1.682207se=1.682207 Find the 95% confidence interval for the average number of sick days an employee will take per year, given the employee is 26. Round your answer to two decimal places.
The data show the chest size and weight of several bears. Find the regression equation, letting chest size be the independent (x) variable. Then find the best predicted weight of a bear with a chest size of 58 inches. Is the result close to the actual weight of 572 pounds? Use a significance level of 0.05. Chest size (inches) 46 57 53 41 40 40 Weight (pounds) 384 580 542 358 306 320 LOADING... Click the icon to view the critical values of the Pearson correlation coefficient r. What is the regression equation? y=nothing+nothingx (Round to one decimal place as needed.)
Jump to... Which one of the following statements about the distribution of the sample proportion is false? Select one: a. The distribution of the sample proportion is approximately normal for large sample sizes. b. The mean of the sample proportion is equal to the population proportion of successes, p. c. The variance of the sample proportion always decreases as the population proportion of successes decreases. d. The variance of the sample proportion is equal to p(1-p) divided by the sample size, n. e. As the population proportion increases, the mean of the sample proportion increases. Previous page Nex
Greg actually has a GPA of 4.60 What is the residual score? A) 2.59 B) -4.06 C) -3.06 D) 1.42 How much of the variance in GPA can be explained by the variance in social contacts? A) 20.00% B) 40.00% C) 16.00% D) 63.24% What is the standard error of the estimate? A) 2.23 B) 3.35 C) 2.43 D) 3.07
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QUADRATIC REGRESSION 2) Road & Track provides the following sample tire wear and maximum load capacity for automobile tires. (IMG 1) A. Find the coefficient of determination. comment on it B. Find the equation of the regression parabola and calculate the estimated data for each value of the independent variable. C. Determine the residual variance, the standard error of estimate, and the explained variance. comment them
6. One of the most important uses of a regression line is; a. to determine if any x-values are outliers. b. To know the relation between the random variables. c. to determine if any y-values are outliers. d. to estimate the unknown parameters. e. to estimate the change in y for a one-unit change in x. 7. The estimated simple linear regression model represents: a. the strength of the relationship between x and y b. the expected x value when y is zero c. the expected y value when x is zero d. a population parameter. e. None of the above. 8. A chi-square test involves a set of frequencies called observed frequency and expected frequency. What are the observed frequencies? a. Hypothetical frequencies that would occur of the alternative hypothesis were true. b. Hypothetical frequencies that would occur if the null hypothesis were true. c. The actual frequencies that did occur in the given experiment. d. The long-run counts that would be expected if the observed counts are representative. e.…
a. Determine the correlation coefficient between the number of periods and the sales. Is time series a good method of predicting the monthly sales for year 4?b. Determine the correlation coefficient between the sales and the number of tourists in the area. Is a linear regression a good method to predict the sales for a month?

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Q5. The random error for the sample regression model, denoted by e, is equal to the: A) predicted value of y minus the estimated value of y B) estimated value of y minus the predicted value of y C) actual value of y minus the predicted value of y D) actual value of y minus the actual value of x