& Obtain the regression equations from the data given below: 1 2 9 8 3 4. 6. 8 10 12 11 13 14 16 15 Enter textPlot the regression equati on on a graph paper and determine X and Y Also calculate the value o f correlation coefficient.
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- Which of the following best describes a regression coefficient in a bivariate setting? a. The change in Y predicted by a unit change in X b. The slope of a line that minimizes the sum of squared residuals c. The correlation coefficient multiplied by SDy/SDx d. All of the aboveIn exercise 1, the following estimated regression equation based on 10 observations was presented. y^=29.1270+.5906x1+.4980x2Develop a point estimate of the mean value of y when x1=180 and x2=310. Predict an individual value of y when x1=180 and x2=310.b.Find the linear correlation coefficient, r, then determine whether there is sufficient evidence to support the claim of a linear correlation between the two variables. c. find the critical values
- A sample of n = 15 pairs of X and Y scores produces a Pearson correlation of r = 0.45, SSY = 90. a) If the regression equation was found for these scores, how much of the Y variability would be predicted by the regression equation (SSregression) and how much would not be predicted (SSresidual)? b) Does the regression equation predict a significant portion of the variability for the Y scores? (Equivalently, is the Pearson correlation significant?)A professor obtains SAT scores and freshman grade point averages (GPA) for a group of n=15 college students. The SAT scores have a mean of M=580 with SS=22,400, and GPA has a mean of 3.10 with SS=1.26, and SP=84. a. Find the regression equation for predicting GPA from SAT scores. b. What percentage of the variance in GPA is accounted for by the regression equation? (Compute the correlation, r, then find r2.) c. Does the regression equation account for a significant portion of the variance in GPA? Use α=.05 to evaluate the F-ratio.A professor obtains SAT scores and freshman grade point averages (GPAs) for a group of n = 15 college students. The SAT scores have a mean of M = 580 with SS = 22,400, and the GPAs have a mean of 3.10 with SS = 1.26, and SP = 84. A) Find the regression equation for predicting GPA from SAT scores. B) What percentage of the variance in GPAs is accounted for by the regression equation (i.e., compute the correlation, r, then find r2)? C) Does the regression equation account for a significant portion of the variance in GPA? Use a = .05 to evaluate the F-ratio.
- A professor obtains SAT scores and freshman grade point averages (GPAs) for a group of n=15 college students. The SAT scores have a mean of M=580 with SS = 22,400, and the GPAs have a mean of 3.10 with SS = 1.26, and SP = 84. Find the regression equation for predicting GPA from SAT scores. What percentage of the variance in GPAs is accounted for by the regression equation? (Compute the correlation, r, then find r2.) C) Does the regression equation account for a significant portion of the variance in GPA? Use alpha = 0.05 to evaluate the F-ratio. A) b=0.00375; a=0.925; Y (hat) = 0.00375X+0.925 B) r= 0.5 r^2= 0.25The following data shows the dexterity test scores of five assembly-line employees of Dimples Company Limited and their respective hourly productivity.Employee Score on dexterity test (?) Ali 12Kofi 14Kwesi 17Abudu 16Nana 11Units produced in an hour (?) 55636770 51You are required to(i) Write the regression equation(ii) Interpret the regression equation(iii) Calculate the Pearson’s Product Moment Correlation Coefficient.(iv) Interpret the correlation coefficient (v) Suppose the dexterity test score is 13, what would be the units produced in an hour? (vi) Clearly explain (in detail) the difference between regression analysis and correlation analysis.A group of students measure the length and width of a random sample of beans. They are interested in investigating the relationship between the length and width. Their summary statistics are displayed in the table below. All units, if applicable, are millimeters. Mean width: 7.555 Stdev width: 0.914 Mean height: 12.686 Stdev height: 1.634 Correlation coefficient: 0.8203 d) If the students are interested in using the height of the beans to predict the width, calculate the slope of this new regression equation. e) Write the equation of the best-fit line that can be used to predict bean widths. Use x to represent height and y to represent width.
- A regression between foot length(response variable in cm) and height (eexplanatory variable in inches) for 33 students resulted in the following regression equation: y^=10,9+0,23X one student in the sample was 73 inches tall with a foot length of 29cm.What is the predicted foot length for A)33cm B)17,57cm C)27,69cm D)29cmFind the Pearson r Correlation Coefficient: r = Blank 1 Find the equation of the regression line: y = Blank 2x + Blank 3 Predict power consumption for an ambient temperature of 65 °F: Blank 4 BTUA set of n = 4 pairs of X and Y values has a Pearson correlation of r = 0.60 and SSY = 200. The standard error of estimate for the regression equation is _______. a. 8 points b. 10 points c. 6 points d. 4 points