a. What is a residual?b. In what sense is the regression line the straight line that "best" fits the points in a scatterplot?a. What is a residual?O A. A residual is a value that is determined exactly, without any error.O B. A residual is the amount that one variable changes when the other variable changes by exactly one unit.O C. A residual is a point that has a strong effect on the regression equation.OD. A residual is a value of y-ŷ, which is the difference between an observed value of y and a predicted value of y.b. In what sense is the regression line the straight line that "best" fits the points in a scatterplot?The regression line has the property that theof the residuals is thesum of squaressumpossible sum.

Since we know that residual is defined as : The residual is the difference between the actual value…

Answered: a. What is a residual? b. In what sense…

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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Use the scatterplot of Vehicle Registrations below to answer the questions Vehicle Registrations in the United States, 1925- 2011 Vehicles millions 300 y = 3.0161x - 5819.5 R? = 0.9695 250 200 150 100 50 1920 -50 1940 1960 1980 2000 2020 Year Write a sentence explaining the value of the slope for this regression line. For every increase in year, the number of vehicle registrations in the US increases by 3.0161 million. For every increase in year, the number of vehicle registrations in the US increases by 5819.5. For every increase in vehicle registrations in the US, the number of years increases by 5819.5. For every increase in vehicle registrations in the US, the number of years increases by 3.0161 million. Registrations (in millions)
Q2. Adjusted R2 is the modified version of R after adjusting for the number of predictor variables in a multiple regression model. a. TrueB. FalseC. None of the above
The OLS estimator is derived by A. making sure that the standard error of the regression equals the standard error of the coefficient estimator. B. minimizing the sum of squared regression. C. minimizing the sum of squared error. D. connecting the Y; corresponding to the lowest X; observation with the Y; corresponding to the highest X; observation. Decat Celoction O O
A vocational counselor uses the number of days without employment to predict her clients' feelings of self efficacy, measured on a scale of 1 to 5, with higher numbers meaning that clients feel more secure in their job related abilities. The slope of the regression line is –1.02. Which statement is the best interpretation for this finding? a. For every 1-point increase in self-efficacy, there is an associated decrease in the number of days of unemployment. b. For every additional day of unemployment, there is an associated decrease in self-efficacy of 1.02 points. c. The least number of days a person can be unemployed and still feel self-efficacious is 3.98 points d. The decrease in self-efficacy of 1.02 points is caused by each additional day of unemployment
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1. School administrators believe their freshman applications are influenced by two variables: tuition and the size of the applicant pool of eligible high school seniors in the state. The following data for an 8-year period show the tuition rates (per semester) and the sizes of the applicant pool for each year: Tuition in pesos Applicants Pool Applicants 27000 76,200 11,060 37500 78,050 10,900 41250 67,420 8,670 42000 70,390 9.050 46500 62,550 7,400 48750 59,230 7,100 52500 57,900 6,300 57900 60,080 6,100
Question. Using the following regression result, make your answers to the questions. Call: Im(formula - wage - educ, data - data) Residuals: 10 Median -5.1579 -2.5066 0.3816 2.4539 4.4737 Min 30 Max Coefficients: Estimate Std. Error t value Pr(>1tl) (Intercept) 9.0526 educ 5.1420 1.761 0.11635 2.1842 0.5994 3.644 0.00655 ** --- Signif. codes: 0 ***** 0.001 *** 0.01 ** 0.05 . 0.1' 1 Residual standard error: 3.305 on 8 degrees of freedom Multiple R-squared: 0.6241, F-statistic: 13.28 on 1 and 8 DF, p-value: 0.006549 Adjusted R-squared: 0.5771 1) Using the estimate and standard error of educ variable, perform the following hypothesis test. Ho:Beduc = 0 H1: Beduc # 0 2) Interpret the above hypothesis test result.
Using data from 50 workers, a researcher estimates Wage Be + B₁Education + B2Experience + B3Age +, where Wage is the hourly wage rate and Education, Experience, and Age are the years of higher education, the years of experience, and the age of the worker, respectively. A portion of the regression results is shown in the following table. Coefficients Standard Error t Stat p-Value Intercept 7.45 3.79 1.97 0.0554 Education 1.06 0.37 2.86 0.0063 Experience 0.37 0.18 2.06 0.0455 Age -0.02 0.06 -0.33 0.7404 a-1. Interpret the point estimate for ẞ1. As Education increases by 1 year, Wage is predicted to increase by 1.06/hour. As Education increases by 1 year, Wage is predicted to increase by 0.37/hour. As Education increases by 1 year, Wage is predicted to increase by 1.06/hour, holding Age and Experience constant. As Education increases by 1 year, Wage is predicted to increase by 0.37/hour, holding Age and Experience constant. a-2. Interpret the point estimate for ẞ2. ○ As Experience…
2. Participants were kept awake for a certain number of hours before given a visuospatial task. Researchers measured how many correct responses each participant had. Results are shown below. Use alpha = .01. Number of Correct Hours Kept Awake (X) Responses (Y) 21 X = 10 SS, = 422 Y = 10 SS, = 690 2 4 19 %3D 6. 13 SPxy =-525 ху 5 20 S, =5.70 S, = 7.29 9. 11 10 9. 14 5 15 5 17 2 18 1 17 1 13 4 18 8 11 A. Graph the data. B. State the hypotheses. C. Make a decision about the null. a. Calculate Pearson's r i. Decision about null hypothesis? b. Calculate effect size i. Interpret effect size. D. State your conclusion. E. Relate your conclusion to the research. F. Calculate the regression formula. G. If someone was kept awake for 9 hours, what is the predicted number of correct responses?
Cost Number 85 4 2 10 52 55 68 67 86 83 73 13. What is the value of the pearson.coefficient? 14. What is the slope of the regression line? 15. Which of the following is estimated number of products sold when the cost of the advertisement is 12,000 dallars A. 89250 B. 33517 C. 4283 D. 15
1. y=____+______x (Round to two decimal places as needed.) 2. Identify a characteristic of the data that is ignored by the regression line. A.There is no trend in the data. B.The data has a pattern that is not a straight line. C.There is an influential point that strongly affects the graph of the regression line. D.There is no characteristic of the data that is ignored by the regression line.

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