2. Danford et al. (1960) gave an example of a covariance matrix on41 degree of freedom.; the variable was time (in days) after radiation. Thevariances and covariances wereS =4685 4522 5096 5202 5035 4746 5026 5090 4847 49334799 5287 5408 5250 5026 5323 5280 5238 522861516192 6055 5773 6120 6092 6027 61326525 6231 5923 6285 6204 6137 62526171 5850 6185 6150 6105 61755745 5941 6000 5950 595964796332 6371 63826523 6398 63906798 65666753(a) Can an intraclass correlation model be assumed? Test at α = 0.05.(b) Are the scores for each time period independent? Test at a = = 0.05.(c) Does the result of (b) seem reasonable?(d) Perform an equicorrelation test for the covariance matrix.(e) Perform a sphericity test for the covariance matrix.

Step 1:(a) Intraclass Correlation Model:The intraclass correlation coefficient (ICC) assesses the…

Answered: 2. Danford et al. (1960) gave an…

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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Which of the following should be used to assess the collinearity among explanatory variables condition. (Select all that apply) a residual plot of the residuals versus predicted values a scatterplot matrix a correlation matrix a normal probability plot of the residuals
5
The National Safety Council released the following data on the incidence rates for fata or lost-worktime injuries per 100 employees for eight industries in three recent years. Compute the covariance between each pair of years (2018 and 2019), (2018 and 2020) and (2019 and 2020). Compute the coefficient of correlation (r) for each pair of years and determine which years are most highly correlated.
answer the following attched question 2 with all parts
How to interpret the following correlation matrix X1 X2 X3 X4X1 1 X2 -0.026651075 1 X3 -0.251215273 0.478429673 1 X4 0.009303729 0.185917439 -0.126481433 1
1.The least squares estimate of β0 is i. 2.3176 ii. 0.7176 iii. 0.8824 iv. 1.8990 2. The least squares estimate of β1 is i. 0.4773 ii. 0.2990 iii. 0.2061 iv. 0.9265 3. The linear correlation coefficient r is i. 0.4122 ii. 0.1700 iii. 0.2990 iv. 0.5683
Ensure the RaceResults worksheet is active, then use the FREQUENCY function to calculate the frequency distribution of the race results in column D. Place your results in the range G4:G9. Enter a function in cell F22 to calculate the correlation between age (Columns C) and race time (Column D). Enter a function in cell G22 to calculate the covariance between age and race time. Enter a function in cell H22 to calculate the variance of the ages in the data set. Note this is a sample of data not a population. Enter a function in cell 122 to calculate the standard deviation of the ages in the data set.
1. Suppose a X value is produced by a random process that has a mean of 1 and a variance of 9, while a Y value is produced by a random process that has a mean of 9 and a variance of 1. Let Z = 3X - 2Y. Compute: a. the mean and variance of Z assuming X and X are independent. b. the mean and variance of Z assuming X and X are not independent and their correlation coefficient is 0.50.
4) The following data gives the distribution of scores of 10 students in mathematics and statistics in a test. Find the correlation coefficient r (X,Y). Scores in Mathematics(X): 27 31 32 26 37 Scores in Statistics (Y): 31 34 26 32 37 a) - 0.359 b) 0 - 0.953 c) - 0.539 d) - 0.395 35 35 26 28 29 38 32 39 33 32
According to the information given below, compute the correlation coefficient and the covariance coefficient between stock A and stock B. Standard deviation of the portfolio (stock A and stock B) : 0.37 Standard deviation of the stock A : 0.38 Standard deviation of the stock B : 0.43 Weight for stock A : 0.60 Weight for stock B : 0.40
An investigator has a data set which contains a response variable(y) and four explanatory variables(xı, x2, X3, X4). A correlation matrix was produced from the data set and is provided below. Correlations Y X1 X2 X3 X1 0.785 X2 0.731 0.690 X3 0.603 0.343 0.771 Х4 0.745 0.742 0.500 0.630 Does the correlation matrix provide evidence that multicollinearity may be an issue? Explain your reasoning.

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