Y1.932.551.722.482.871.871.343.032.542.341.41.451.723.82.131.812.332.532.043.2X1565525477555502469517555576559574578548656688465661477490524X2327111341NT2N0040061228852 For item 10 to 14.The following data were collected to determine the relationshipbetween the GPA(Y), entrance aptitude exam score(X1) and rank(X2) inclass of selected students taking MBA.Using t-test statistic and rank correlation of Y and X2, test thehypothesis at 5% level of significance.The decision isO Accept Ho, there is no significant relationship between Y and X2.Reject Ho, there is a significant correlation between Y and X1.O Reject Ho, there is no significant correlation between the GPA and rank inclass of MBA students.O Accept Ho, there is a significant relationship between Y and X1.Reject Ho, there is a significant correlation between the GPA and the rank inclass of MBA students.

Correlation is the measure that determines the degree of strength of association between the two…

Answered: The following data were collected to…

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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In each of Exercises, use the technology of your choice to decide whether you can reasonably apply the correlation t-test. If so, perform and interpret the required correlation t-test(s) at the 5% significance level.Shortleaf Pines. The data from Exercise for volume, in cubic feet, and diameter at breast height, in inches, of 70 shortleaf pines are on the WeissStats site. Do the data provide sufficient evidence to conclude that diameter at breast height and volume are positively linearly correlated for shortleaf pines?ExerciseWorking with Large Data SetsIn Exercises, use the technology of your choice toa. obtain and interpret the standard error of the estimate.b. obtain a residual plot and a normal probability plot of the residuals.c. decide whether you can reasonably consider Assumptions 1–3 for regression inferences met by the two variables under consideration.Shortleaf Pines. The ability to estimate the volume of a tree based on a simple measurement, such as the diameter of the…
Listed below are the overhead widths (in cm) of seals measured from photographs and the weights (in kg) of the seals. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the critical values ofr using a = 0.05. Is there sufficient evidence to conclude that there is a linear correlation between overhead widths of seals from photographs and the weights of the seals? Overhead Width 7.2 7.6 9.6 9.3 8.7 8.1 Weight 118 189 242 199 199 184
Researchers conducted a study to determine the effects of different types of alcohol on the peak alcohol concentration. In one part of the study, the researchers gave 15 randomly select males a controlled volume of vodka and monitored the subjects' alcohol concentration following the period of consumption. The legal limit for driving is 80 mg/dL (milligrams per deciliter of blood). A hypothesis test was conducted to see if the mean peak alcohol concentration from drinking vodka was different from the legal driving limit. This was reflected in the null and alternative hypotheses ?0:??1:?=80 mg/dL≠80 mg/dL The researchers required their results to be statistically significant at a level of ?=0.10. The mean peak alcohol concentration of the participants after drinking a controlled volume of vodka was 77.4 mg/dL with a standard deviation of 17.25 mg/dL. Determine the confidence interval that corresponds to the ?‑test. Give the lower and upper bounds precise to two decimal places
The weights (in pounds) of 6 vehicles and the variability of their braking distances (in feet) when stopping on a dry surface are shown in the table. Can you conclude that there is a significant linear correlation between vehicle weight and variability in braking distance on a dry surface? Use a = 0.05. Weight, x Variability in braking distance, y 5980 5370 6500 5100 5820 4800 1.72 1.97 1.87 1.63 1.64 1.50 Click here to view a table of critical values for Student's t-distribution. Setup the hypothesis for the test. Ho: Ha: P Identify the critical value(s). Select the correct choice below and fill in any answer boxes within your choice. (Round to three decimal places as needed.) O A. The critical value is. B. The critical values are - to and to %3D Calculate the test statistic. t= (Round to three decimal places as needed.) What is your conclusion? There enough evidence at the 5% level of significance to conclude that there a significant linear correlation between vehicle weight and…
In baseball, is there a linear correlation between batting average and home run percentage? Let x represent the batting average of a professional baseball player, and let y represent the player's home run percentage (number of home runs per 100 times at bat). A random sample of n = 7 professional baseball players gave the following information.
D Correlation coeff, r: 0.961961 Fifty-four wild bears were anesthetized, and then their weights and chest sizes were measured and listed in a data set. Results are shown in the accompanying Correlation Results display. Is there sufficient evidence to support the claim that there is a linear correlation between the weights of bears and their chest sizes? When measuring an anesthetized bear, is it easier to measure chest size than weight? If so, does it appear that a measured chest size can be used to predict the weight? Use a significance level of a=0.05. Critical r: +0.2680855 P-value (two tailed): 0.000 C -- there is not a linear correlation between the two. OB. Yes, it is easier to measure a chest size than a weight because measuring weight would require lifting the bear onto the scale. The chest size could not be used to predict weight because there is too much variance in the weight of the bears. OC. Yes, it is easier to measure a chest size than a weight because measuring weight…
A data set contains information on the grams of fat and number of calories in 24 different fast foods. The correlation coefficient between fat content and calories is determined to be -0.63. Calculate the p-value for the test of significance.
find linear correlation coefficient, P value, and test statistic.
A random sample of 7 countries gave the following figures for X = annual per capita income and Y = urbanization rate (percentage of people living in urban area): Country X (US dollars) Y (%) 1 3500 20 2 2700 24 3 2100 16 4 2400 19 5 3000 26 6 2000 19 7 1900 17 Calculate the correlation coefficient for the sample. Explain the results At the 5% significant level, test whether per capita income and urbanization rate are unrelated.
what are the critical values r =?
The table below includes data from taxi rides. The distances are in miles, the times are in minutes, the fares are in dollars, and the tips are in dollars. Is there sufficient evidence to conclude that there is a linear correlation between the time of the ride and the tip amount? Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value of r. Determine whether there is sufficient evidence to support a claim of linear correlation between the two variables. Use a significance level of a = 0.01. Does it appear that riders base their tips on the time of the ride? Click here for information on the taxi rides. Construct a scatterplot. Choose the correct graph below. O A. Tip Amount ($) 25- Q 0 35 G Ride time (minutes) Determine the linear correlation coefficient. The linear correlation coefficient is r= (Round to three decimal places as needed.) Tip Amount ($) B. 25- 0- 0 35 G Ride time (minutes) Taxi data ip Amount (S C. 25- 0- 35 Ride time…
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