Analyze at least two of the X variable’s correlation level with Y variable.  Explain the correlation based upon the p test. Use the summary output for the data, which is found below: SUMMARY OUTPUT                                   Regression Statistics               Multiple R 0.807187704               R Square 0.651551989               Adjusted R Square 0.644440805               Standard Error 143.9428959               Observations 51                                 ANOVA                   df SS MS F Significance F       Regression 1 1898399.614 1898399.614 91.62356067 8.42534E-13       Residual 49 1015258.307 20719.55729           Total 50 2913657.922                                 Coefficients Standard Error

use statcrunch to show work

pare percentage differences between 2 or more categories of an independent variable), the following statistical test should be used: a. Simple linear regression b. Pearson correlation coefficient c. T test d. Chi-square test

State Debt and Per Capita Tax Data for per capita state debt and per capita state tax for nine randomly selected states are shown. The correlation coefficient is r=0.463. Compute the standard error of the estimate rounded to at least two decimal places, if appropriate. Assume a=0.05. Per capita debt x Per capita tax y Send data to Excel 4529 1455 2349 3478 1948 2387 2423 3357 1645 1430 O The standard error of the estimate should be calculated. Sest O The standard error of the estimate should not be calculated. X 1902 3691 1913 2054 2069 2049 3 907 2054

A regression analysis was performed and the summary output is shown below.   Regression Statistics Multiple R 0.7802268560.780226856 R Square 0.6087539470.608753947 Adjusted R Square 0.5870180550.587018055 Standard Error 6.7217061336.721706133 Observations 20     ANOVA   dfdf SSSS MSMS F� Significance F� Regression 11 1265.3871265.387 1265.3871265.387 28.006928.0069 4.9549E-054.9549E-05 Residual 1818 813.264813.264 45.18145.181     Total 1919 2078.6512078.651           Step 2 of 2:  Which measure is appropriate for determining the proportion of variation in the dependent variable explained by the set of independent variable(s) in this model?

Using the linear correlation coefficient given above, calculate and give the value of the coefficient of determination. Explain in a sentence what this means in the context of this example, treating gpa as a predictor.

Use the following ANOVA table for regression to answer the questions. Response: Y Source DF Sum Sq Mean Sq F-value Pr(>F) Regression 1 351.47 351.47 13.32 0.000 Residual Error 359 9474.01 26.39     Total 360 9825.48                 Give the F-statistic and p-value.Enter the exact answers.The F-statistic is .The p-value is .

Identify the correlation coefficient r:  critical values:  round to 3 decimals please

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 display. Use a significance level of x = 0.05 to answer the following questions. Correlation Results Correlation coeff, r: Critical r: P-value (two tailed): 0.000 Identify the correlation coefficient, r. r= (Round to three decimal places as needed.) Identify the critical value(s). (Round to three decimal places as needed.) OA. There are two critical values at r= ± OB. There is one critical value at r= Is there sufficient evidence to support the claim that there is a linear correlation between the weigh of bears and their chest sizes? Choose the correct below and, if necessary, fill in the answer box within your choice. (Round to three decimal places as needed.) exceeds the critical value. A. No, because the absolute value of r= OB. Yes, because the absolute value of r= OC. No, because r= exceeds the positive critical value. falls…