Given the following table, use the matrix method to derive the constant and slope parameters of the sample regression function: Module test mark = f (Weekly study hours). X and Y stand for weekly study hours and module test mark respectively. X (Weekly study hours) Y (Module test mark) 1 40 2 40 3 45 4 60 5 70

Given the following table, use the matrix method to derive the constant and slope parameters of the sample regression function: Module test mark = f (Weekly study hours). X and Y stand for weekly study hours and module test mark respectively. X (Weekly study hours) Y (Module test mark) 1 40 2 40 3 45 4 60 5 70

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Similar questions

The difference between a regression weight and a beta weight is: A regression weight assumes linearity. A beta weight is for the population while a regression weight is for the sample. A regression weight is less biased. A beta weight is a standardized regression weight.
Independent variable data is listed in cells B2 through B100, and dependent variable data is in cells C2 through C100. Which spreadsheet function would calculate the slope of a linear regression model of this data? Group of answer choices =SLOPE(B2:B100,C2:C100) =SLOPE(C2:C100,B2:B100) =SLOPE(B2,C2) =SLOPE(C2,C100,B2,B100)
Find the equation of the least-squares regression line ŷ and the linear correlation coefficient r for the given data. Round the constants, a, b, and r, to the nearest hundredth. {(1, 4), (3, 6), (5, 11), (7, 15), (11, 23)}
Amount of fertilizer (x) in pounds for each plot: 12, 5, 15, 17, 20, 14: Bushels of tomatoes harvested (y) 24 22 31 33 21 28: Round all values to three decimal places. a) Find the equation of the regression line (line of best fit). b) Calculate the correlation coefficient (r). c) Determine if there is a significant linear correlation. d) If the linear relation is significant, predict how many bushels of tomatoes would be harvested if 22 pounds of fertilizer was used.
The following table shows students’ number of absences, x, and the student’s final grade,, y.# of absences x 6 2 15 9 12 5 8 Final grade y 82 86 43 74 58 90 78a) Calculate r, the correlation coefficient ________________b) Find the equation of the regression line __________________________________c) If a student is absent 4 times,, what grade does your regression line predict?__________________
11. For temperature (x) and number of ice cream cones sold per hour (y). (65, 8), (70, 10), (75, 11), (80,13), (85, 12), (90, 16). Interpret the coefficient of determination. Optional Answers: 1. 88.2% of the variability in the number of cones sold is explained by the least-squares regression model. 2. 93.9% of the variability in the number of cones sold is explained by the least-squares regression model. 3. 88.2% of the variability in the temperature is explained by the least-squares regression model. 4. 93.9% of the variability in the temperature is explained by the least-squares regression model.
Which of the multivariate regression parameters listed below would be best interpreted as: the proportion of variation in the dependent variable explain by all the independent variables in the model. a b1 X1 R2
d. Draw the regression line on the scatter diagram using the yp points.e. Find y for x = 50 x 20 10 30 40 60 70 y 20 20 30 50 60 80
For the paired data below, do a complete regression analysis: a) Compute the value of the correlation coefficient. b) Use the Critical Value (CV) from the table to determine if there is a significant linear correlation. c) Determine the linear regression equation.