The correlation coefficient r=0.15, is given for a sample of n= 13 data points. Use the a = 0.05column in the figure to the right to determine whether or not we may conclude that a correlationdoes exist in the population. (Using the a = 0.05 column there is a probability of 0.05 that thevariables are not really correlated in the population and our results could be attributed to chance.Ignore this possibility when concluding whether or not there is a correlation in the population.)a=.050.950=.054.19 0.45650.87820 0.44422 0.42327 0.3816.0.8110.75480.707320.3490.3250.30490.66637100.63242Choose the correct answer below.110.602470.288120.576520.273O A. Correlation does exist130.553620.250140.53272 0.232O B. Correlation does not exist1516170.5148292 0.205102 0.1950.2170.4970.482180.468O TimMAR18MacBook Air

From the given table of critical values, we go for n = 13 and alpha = 0.05, we get Critical value =…

Answered: The correlation coefficient r=0.15, is…

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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4. Compute the Pearson correlation for the following data. X Y 3 1 4 5 2 A researcher is interested in seeing if there is a significant relationship between the number of hours of sleep a night (X) and Productivity scores (Y). She conducts a study to test her hypothesis. Please use the data set above. a. Use a two-tailed test with a = .05. Conduct the four steps for hypothesis testing and label each step: Stepl, Step 2, Step 3, and Step 4. b. Write a sentence regarding your results. c. Calculate the regression equation for this data set. d. What are the predicted Y scores for the following X scores: X=1, X=7, X=10, X-12. 2364n
Compute the Pearson correlation for the following data.X: 2, 3, 6, 4, 5 Y :3, 1, 5, 4, 2 A researcher is interested in seeing if there is a significant relationship between the number of hours of sleep a night (X) and Productivity scores (Y). She conducts a study to test her hypothesis. Please use the data set above. Use a two-tailed test with a = 0.1. Conduct the four steps for hypothesis testing and label each step: Step1, Step 2, Step 3, and Step 4.
Which of the following is not a cause of perfect multicollinearity? Select all that apply. One of the explanatory variables is equal to half of another explanatory variable for 100% of the observations in the sample. The correlation between two of the explanatory variables is 1.00. One of the explanatory variables is equal to half of another explanatory variable for 20% of the observations in the sample. A dummy variable for male is included at the same time as a dummy variable for non-male. One of the regressors is X and another regressor is X².
If you read that the value of a Pearson r is 0.45, p = 0.09, should you have confidence that this correlation represents the actual situation in the population? a. Yes, because both r value was greater than 0.05. b. No, because the probability of error was greater than 0.05.
A study was done to look at the relationship between number of lovers college students have had in their lifetimes and their GPAS. The results of the survey are shown below. Lovers GPA 6 3 4 4 7 6 2.2 2.2 2.3 2 2 3.4 3.8 1.9 2.3 a. Find the correlation coefficient: r= Round to 2 decimal places. b. The null and alternative hypotheses for correlation are: Ho: Hj: ?v + 0 = 0 The p-value is: (Round to four decimal places) c. Use a level of significance of a = 0.05 to state the conclusion of the hypothesis test in the context of the study. O There is statistically insignificant evidence to conclude that a student who has had more lovers will have a lower GPA than a student who has had fewer lovers. There is statistically significant evidence to conclude that a student who has had more lovers will have a lower GPA than a student who has had fewer lovers. O There is statistically significant evidence to conclude that there is a correlation between the number of lovers students have had in…
The scatterplot below shows the relationship between two random variables X and Y. (a) Is the correlation a good metric for describing the relationship between X and Y for these data? Why or why not? Regardless of your answer suppose you calculated the sample correlation between X and Y and found that r = -0.15. Explain in one sentence what this means. (b) If, as noted in (a), r = -0.15 then what is the value of the correlation between 2X and 5Y? (c) Based on (b) draw your best approximation to the least squares regression line that fits the data above. Also, make a rough sketch of the corresponding residual plot.
For a data set of weights (pounds) and highway fuel consumption amounts (mpg) of five types of automobile, the linear correlation coefficient is found and the P-value is 0.033. Write a statement that interprets the P-value and includes a conclusion about linear correlation. The P-value indicates that the probability of a linear correlation coefficient that is at least as extreme is nothing%, which is ▼ high, low, so there ▼ is not is sufficient evidence to conclude that there is a linear correlation between weight and highway fuel consumption in automobiles.
Which of the following represents the strongest correlation? O.10 00 O.55 O-.24
Given that the variances of random variables X and Y are 484 and 625, respectively. The correlation between X and Y is -0.52. Find Var (X-Y).

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