The Pearson correlation between X and Y is r = 0.40. When a second variable, X₂, is added to the regression equation, we obtain R2 = 0.64. How much variance for the Y scores is predicted by using both X and X₂ as predictorvariables?O 0.40 or 40%O 0.64 or 64%O 0.48 or 48%O 0.16 or 16%

Given that Pearson correlation coefficient (r)=0.40 If the second variable X2 is added to the…

Answered: e Pearson correlation between X and Y…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

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Problem 1P

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Suppose that you run a correlation and find the correlation coefficient is 0.317 and the regression equation is 36.127.2x. ŷ = The mean for the data values was 7.1, and the mean for the y data values was 15. AT Test for the slope of the regression line is performed, and the p-value is greater than the level of significance of 0.05. Use the appropriate method to predict the y value when x is 8.5.
A psychology professor studies the relationship between anxiety(X) and test performance (Y). Ten students take an anxiety questionnaire prior to taking the final exam. Below is the SPSS printout of the regression equation. Correlations Anxiety FinalExam Anxiety Pearson Correlation 1 -.691* Sig. (2-tailed) .027 N 10 10 FinalExam Pearson Correlation -.691* 1 Sig. (2-tailed) .027 N 10 10 *. Correlation is significant at the 0.05 level (2-tailed). ANOVAa Model Sum of Squares df Mean Square F Sig. 1 Regression 861.959 1 861.959 7.301 .027b Residual 944.441 8 118.055 Total 1806.400 9 a. Dependent Variable: FinalExam b. Predictors: (Constant), Anxiety Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 125.883…
The following data shows the height children with time: Age X, in |(months) Height Y, in ( cm) 18 19 20 21 22 76.1 77.0 78.1 78.2 78.8 The regression equation, correct to 3 decimal place is Drag and drop the correct answer. Y = 0.517X + 55.876 Y = 0.688X + 63.927 Y = 0.635X + 64.928 Y = 0.669X + 62.216 %3D
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4
12. A consumer advocacy group recorded several variables on 140 models of cars. The resulting information was used to produce the following regression output that relates the city gas mileage (in mpg) and the engine displacement (in cubic inches). The regression equation is mpg:city= 33.4 0.0624 displacement Predictor Constant SE Coef T P 0.7762 43.00 0.000 displacement -0.0624 0.003810 0.000 S 3.13923 = R-Sq 66.0% R-Sq (adj) = 65.8% a. We have a car that has an engine with 150 cubic inches. Based on this output, what city gas mileage would you predict for this car? Coef 33.4 b. Based on this output what is the correlation between city gas mileage and displacement? C. I value: The test statistics for testing the slope is zero is missing. Calculate this The group o also recorded the power of the engine (in horsepower) for each car. The following regression output was produced. Predictor Constant horsepower The regression equation is mpg:city = 32.2 0.0572 horsepower Coef SE Coef 32.2 T…
Assuming a linear relationship between X and Y, if the coefficient of correlation (r) equal -0.30, there is no correlation. the slope is negative. variable X is larger than variable Y. O the variance of X is negative.
It is believed that standardized test scores, such as SAT, is a good predictor of first-year college students' GPA. 1200 1120 1000 1420 1280 750 1100 y 3.2 2.5 2.7 3.5 2.9 2.2 2.3 1. Find the the correlation coefficient. Round your final answer to four decimal places. 2. Write the regression equation below. Round all numbers to four decimal places. 3. Using the data shown above, predict a student's first-year GPA when the student scores a 1275 on the SAT. Round your final answer to two decimal places. 4. What percentage of variation in GPAS can be explained by students' SAT scores? Round your final answer to two decimal places.
he data show the chest size and weight of several bears. Find the regression equation, letting chest size be the independent (x) variable. Then find the best predicted weight of a bear with a chest size of 39inches. Is the result close to the actual weight of 126 pounds? Use a significance level of 0.05. Chest size (inches) 44 41 41 55 51 42 Weight (pounds) 213 206 176 309 300 178 Critical Values of the Correlation Coefficient r n α=0.05 α=0.01 NOTE: To test H0: ρ=0 against H1: ρ≠0, reject H0if the absolute value of r is greater than the critical value in the table. 4 0.950 0.990 5 0.878 0.959 6 0.811 0.917 7 0.754 0.875 8 0.707 0.834 9 0.666 0.798 10 0.632 0.765 11 0.602 0.735 12 0.576 0.708 13 0.553 0.684 14 0.532 0.661 15 0.514 0.641 16 0.497 0.623 17 0.482 0.606 18 0.468 0.590 19…
The following table gives the data for the average temperature and the snow accumulation in several small towns for a single month. Determine the equation of the regression line, >= bo + b₁x. Round the slope and y-intercept to the nearest thousandth. Then determine if the regression equation is appropriate for making predictions at the 0.05 level of significance. Critical Values of the Pearson Correlation Coefficient Average Temperatures and Snow Accumulations 42 33 15 44 35 15 34 8 18 25 9 14 28 26 11 25 Average Temperature (°F) Snow Accumulation (in.) 35 43 20 10
1. Write down the multiple regression function?2. What is the multiple correlation and the multiple standard error of estimate?3. What is the coefficient of multiple determination and what does it mean?4. Of the three independent variables, which independent variable is not significant as a predictor (α = 0.05)?
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e Pearson correlation between X and Y is r = 0.40. When a second variable, X₂, is added to the regression equation, we obtain R2 = 0.64. How much variance for the Y scores is predicted by using both X, and X, as predictor riables? O 0.40 or 40% O 0.64 or 64% O 0.48 or 48% O 0.16 or 16%