A mathematics teacher recorded the length of time, y minutes, taken to travel to schoolwhen leaving home x minutes after 7 am on seven selected mornings as follows.102030405060y16272839394851a) Find nand calculate the values of Σ x, Σy, Σxν, Σx3, Σν", (Σx)?,(Σ ν)b) Compute the value of the correlation coefficient, r.c) Explain the relationship between the variables according to your answer in b).d) Find the values of a and b in the equation of the least square regression line and writethe corresponding equation.e) Based on your answer in c), find y' when x is 55.

As per our guidelines we are suppose to answer three sub parts. X Y X*Y X*X Y*Y 0 16 0 0 256…

Answered: A mathematics teacher recorded the…

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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Properties of scaling. Suppose that you want to examine the relationship between wages and experience measured in months rather than years. a) What is the variance of experience in months? Compare this to 1b). b) What is the covariance of wages and experience in months? Compare this to 1d). c) What is the correlation of experience and wages? Compare this to le). d) Prove mathematically that the Corr(cX,Y) = Corr(X,Y) using the properties of summation from class. Show each step of your proof.
Which of the following choices could be the Pearson correlation between the x and y variables shown in the scatter plot shown here? a) .934 b) -.934 c) 1 d) 0
Match each correlation value with its interpretation A. large (strong) negative relationship B. small (weak) positive relationship C. large (strong) positive relationship select 1.r -0.8 select 2.r 0.1 select 3. r = 0.7 7,821 MAR 20 F3 F2 D00 F4 F5 F6 F7 $ % & 4 6 LA 00 %#3
Listed below are the budgets (in millions of dollars) and the gross receipts (in millions of dollars) for randomly selected movies. Answer parts a-c. Budget (x) Gross (y)60 6091 6050 4839 62193 558105 14087 52 a. Find the value of the linear correlation coefficient r.
X1 5.5 2.5 8 3 3 2.9 8 9 4 6.5 5.5 5 6 5 3.5 X2 31 55 67 50 38 71 30 56 42 73 60 44 50 39 55 X3 10 8 12 7 81212585nn6mm 10 10 X4 8 6 9 16 15 17 8 10 4 16 7 12 6 4 4 Y 79.3 200.1 163.2 200.1 146 177.7 30.9 291.9 160 339.4 159.6 86.3 237.5 107.2 155
Which of the following best describes the relationship between the variables on the scatter plot below? 11 10 15 4 3. 2 1 1234 56 7 8 9 10 11 12 13 O A. linear association OB. no association OC. non-linear association OD. linear and non-linear association
Which of the following correlation coefficients might lead a researcher to conclude that there is a weak, but significant, negative linear relation between variables X and Y? a. r=0.99 b. r=0.30 c. r=0 d. r=-0.30 c. r=-0.99
Let x be the average number of employees in a group health insurance plan, and let y be the average administrative cost as a percentage of claims. (b) Would you say the correlation is low, moderate, or strong? positive or negative? a) moderate and positiveb) low and negative c) strong and positived) strong and negativee) low and positivef) moderate and negative As x increases, does the value of r imply that y should tend to increase or decrease? Explain. a) Given our value of r, y should tend to decrease as x increases.b) Given our value of r, y should tend to remain constant as x increases. c) Given our value of r, y should tend to increase as x increases.d) Given our value of r, we cannot draw any conclusions for the behavior of y as x increases.
Consider the bivariate data set with n = 7 observations X -4 1 -6 9. -8 -4 -4 Y 20 60 -10 99 -3 16 18 where a linear relationship between X and Y is investigated. The equation relating Y to X is formulated by Y = Bo + B1X + e and is called the simple linear regression equation. Use your calculator to answer the following questions. Give the values of the least squares estimates Bo Round your answer to the nearest integer. Round your answer to 3 decimal places.
A chi square test tells us: a. Whether two continuous variables are correlated with each other. b. Whether two discrete variables are independent of each other c. The amount of variation in one variable explained by the other d. Which categories of one variable are associated with which categories of the other variable

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