### Using the Following Information#### Coefficients Table- **Intercept:** -12.8094 - **Independent Variable:** 2.1794 #### ANOVA Table| | df | SS | MS | F ||----------------|----|----------|----------|---------|| **Regression** | 1 | 12,323.90 | 12,323.90 | 90.0481 || **Residual** | 8 | 1,604.502 | 136.8550 | || **Total** | 9 | 13,928.4 | | |#### QuestionWhat is the correlation coefficient? ### Educational Multiple Choice Question**Please select the correct answer from the options below:**- **Option A:** 0.9406- **Option B:** -0.9406- **Option C:** 0.8827- **Option D:** 0.8848*Note: This is a standard multiple-choice question designed to test your understanding of numerical values. Please choose the option that best answers the question provided in your study material.*

The correlation Coefficient is denoted by r. Formula : r = √SS_Regression/SST

Answered: Independent variable 2.1794 ANOVA df S…

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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Due Sat 12/05 Here is a bivariate data set. y 20 61 26 61 19 57 25 48 31 48 24 42 36 55 3 35 Find the correlation coefficient and report it accurate to four decimal places. r =
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 10.549 10.549 2.32 0.129 Residual Error 342 1555.074 4.547 Total 343 1565.623 Give the F-statistic and p-value.Enter the exact answers.The F-statistic is .The p-value is . SHOW HINT LINK TO TEXT Choose the conclusion of this test using a 5% significance level. Reject H0. The model is effective. Reject H0. The model is not effective. Do not reject H0. We did not find evidence that the model is not effective. Do not reject H0. We did not find evidence that the model is effective.
|After running the regression analysis between independent and dependent variable the below output is available. SUMMARY OUTPUT Regression Statistics Multiple R 0.714528 R Square 0.510551 Adjusted R Square 0.44937 Standard Error 49.60803 Observations 10 ANOVA ignificance F 1 20536.44 20536.44 8.344902 0.020238 df SS MS F Regression Residual 8 19687.66 2460.957 Total 40224.1 Coefficientsandard Err t Stat P-value Lower 95%Upper 95%ower 95.0%pper 95.0% Intercept -112.208 186.0395 -0.60314 0.563118 -541.216 316.7995 -541.216 316.7995 X Variable 0.398147 0.137827 2.888754 0.020238 0.080319 0.715976 0.080319 0.715976 a. What is the equation of the line? What can you say about the relationship between the two variables?
show how to do it on a TI-84 please and thank you From the data, find the least-squares regression line. What type of correlation is there? Study Hours Test Score 0 20 1 35 2 50 4 47.5 4 65 5 72.5 5 75 6 67.5 6 92.5 7 85 7 90 8 95 5 70 y=9.051+24.765x.y=9.051+24.765x. There is positive linear correlation. y=24.765−9.051x.y=24.765-9.051x. There is negative linear correlation. y=24.765+9.051x.y=24.765+9.051x. There is positive linear correlation. y=−24.765+9.051x.y=-24.765+9.051x. There is negative linear correlation y=9.051−24.765x.y=9.051-24.765x. There is negative linear correlation.
**Please complete table**
enMath Home | My Classes User Settings| Log Out Melissa Washbr Forums Calendar Gradebook divia-sec3 > Assessment Due Fri 04/24/2020 10:00 e: 15 Based on the data shown below, calculate the correlation coefficient (rounded to three decimal places) 9.75 11.3 3. 12.15 4 10.7 9.35 6. 9.6 Lice Points possible: 1 Unlimited attempts. Submit
linear refression
In regression, what is the difference between an observed value of the response variable and its predicted value called? Choose the correct answer below. R2 A standard error A residual A mean square error Leverage
Match the correlation strength on the left side with the correlation score on the right side
Analysis of Variance Source DF SS MS Regression 1 Residual Error 13 0.2364 Total 14 11.3240 What is the value for MSR (Mean Square for Regression)?
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 2020 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 1 of 2: How many independent variables are included in the regression model
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?

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Independent variable 2.1794 ANOVA df S MS F Regression 1 12,323.90 12,323.90 90.0481 Residual 1,604.502 136.8550 Total 13,928.4 What is the correlation coefficient?