Given the following ANOVA table: Source DF MS Regression Error 1 1,800.0 900.0 1,800.00 90.00 20.00 10 Total 11 2,700.0 a. Determine the coefficient of determination. (Round your answer to 3 decimal places.) Coefficient of determination b. Assuming a direct relationship between the variables, what is the correlation coefficient? (Round your answer to 2 decimal places.) Coefficient of correlation c. Determine the standard error of estimate. (Round your answer to 2 decimal places.) Standard error of estimate

Given the following ANOVA table: Source DF MS Regression Error 1 1,800.0 900.0 1,800.00 90.00 20.00 10 Total 11 2,700.0 a. Determine the coefficient of determination. (Round your answer to 3 decimal places.) Coefficient of determination b. Assuming a direct relationship between the variables, what is the correlation coefficient? (Round your answer to 2 decimal places.) Coefficient of correlation c. Determine the standard error of estimate. (Round your answer to 2 decimal places.) Standard error of estimate

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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The data in the table to the right are based on the results of a survey comparing the commute time of adults to their score on a well-being test. Complete parts (a) through (d) below. LOADING... Click the icon to view the table of critical values of the correlation coefficient. a) Which variable is likely the explanatory variable and which is the response variable? Critical Values for Correlation Coefficient n 3 0.997 4 0.950 5 0.878 6 0.811 7 0.754 8 0.707 9 0.666 10 0.632 11 0.602 12 0.576 13 0.553 14 0.532 15 0.514 16 0.497 17 0.482 18 0.468 19 0.456 20 0.444 21 0.433 22 0.423 23 0.413 24 0.404 25 0.396 26 0.388 27 0.381 28 0.374 29 0.367 30 0.361 n (a) Which variable is likely the explanatory variable and which is the response variable? The explanatory variable is…
Here is a bivariate data set. 35.9 78.4 35.5 73.3 38 44.8 40.7 47.5 37.4 55.9 32.4 73.7 29.7 73.5 Find the correlation coefficient and report it accurate to three decimal places. Question Help: Message instructor Submit Question 9MB du
You wish to determine if there is a positive linear correlation between the age of a driver and the number of driver deaths. The following table represents the age of a driver and the number of driver deaths per 100,000. Use a significance level of 0.05 and round all values to 4 decimal places. Driver Age Number of Driver Deaths per 100,000 21 19 27 20 58 31 77 31 47 24 50 26 Ho: ρ = 0Ha: ρ > 0 Find the Linear Correlation Coefficient r = Find the p-value p-value = The p-value is Greater than αα Less than (or equal to) αα The p-value leads to a decision to Reject Ho Accept Ho Do Not Reject Ho
Please please answer both questions. I will really upvote. I know it's not according to your guidelines. Thanks
Listed below are paired data consisting of amounts spent on advertising (in millions of dollars) and the profits (in millions of dollars). Determine if there is a significant linear correlation between advertising cost and profit . Use a significance level of 0.05 and round all values to 4 decimal places. Advertising Cost Profit 3 19 4 16 24 6 29 7 25 27 10 30 Ho: p = 0 На: р * 0 Find the Linear Correlation Coefficient r = Find the p-value p-value = The p-value is O Less than (or equal to) a O Greater than a The p-value leads to a decision to O Do Not Reject Ho O Accept Ho O Reject Ho The conclusion is O There is a significant negative linear correlation between advertising expense and profit. O There is a significant linear correlation between advertising expense and profit. O There is a significant positive linear correlation between advertising expense and profit. O There is insufficient evidence to make a conclusion about the linear correlation between advertising expense and…
The following zero order correlation coefficients are given : r12 = 0.5 r13 = 0.6 r23 =.7 %3D Calculate the multiple correlation coefficients R1,23, R2.13 and R3.12
what are the critical values r =?
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Listed below are paired data consisting of amounts spent on advertising (in millions of dollars) and the profits (in millions of dollars). Determine if there is a significant linear correlation between advertising cost and profit Use a significance level of 0.01 and round all values to 4 decimal places. Advertising Cost Profit 3 21 4 16 5 29 17 7 28 8 21 Ho: p = 0 Ha: p +0 Find the Linear Correlation Coefficient r= Find the p-value p-value = The p-value is Less than (or equal to) a OGreater than a The p-value leads to a decision to Do Not Reject Ho OReject Ho OAccept Ho
We give the total variation, the unexplained variation (SSE), and the least squares point estimate b1 . Total variation = 13.459; SSE = 2.806; b1 = 2.6652 Click here for the Excel Data File Using the information given, find the explained variation, the simple coefficient of determination (r2), and the simple correlation coefficient (r). Interpret r2. (Round your answers to 3 decimal places. Round your percent to 1 decimal place.) Explained variation r2 r % of the variation in demand can be explained by variation in price differential.
A magazine tested paints. The table below shows the overall quality score and cost in dollars per gallon. Use the rank correlation coefficient to test for a correlation between the two variables. Use a significance level of alpha equals 0.05. Based on these results, do you get better quality paint by paying more? a. Calculate the test statistic. r s equals (Round to three decimal places as needed.) b. Find the critical values. r s equals plus or minus (Round to three decimal places as needed.)
Complete the following instructions:i. Identify the independent and dependent variables.ii. Calculate and interpret the Pearson correlation coefficient r for the paired data. Be sure to indicate if the correlation is positive or negative, and whether it is strong, moderate, or weak, or if there does not appear to be any significant correlation. A researcher for a gasoline retailer examines the relationship between the volume of gasoline purchased in kL(i.e. 1000 L) compared to the price of gasoline (in $/L), over a course of several days, to see if there is a correlation between the data: Amount of Gasoline Purchased Price of Gasoline 2.257 1.079 3.126 1.015 2.793 1.046 4.671 0.973 2.137 1.021 5.916 0.939 2.775 0.995 4.88 0.927 3.162 0.964 7.498 0.899 2.971 0.982 3.596 0.945 1.372 1.129 3.961 1.059 i. Independent Variable: Dependent Variable: ii. Pearson correlation coefficient (r): Round to 3 decimal…