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Type numbers in the boxes. Given the following summary statistics, determine the regression equation used to...
Given the following summary statistics, determine the regression equation Type numbers in the bokes. Part 1: 5 points aby Part 2:5 points 1o points used to predict y from x. s,-1.88, sx-37, r--o9, z-20.07, у-79.84 Round all answers to 2 decimal places. Slope- Intercept |
Type numbers in the boxes. Consider the following: Part 1: 10 points ab Part 2: 10 points Part 3: 10 points X 36 61 73 106 124 30 points Y 208 223 176 12 113 1) What is slope of the regression line predicting Y from X, rounded to 2 decimal places? 2) What is the intercept of the regression line predicting Y from X, rounded to 2 decimal places? 3) What is the correlation between X and Y, rounded...
Compute the least-squares regression line for predicting y from x given the following summary statistics, Round the slope and y- intercept to at least four decimal places. I=8.8 5,- 2.2 y = 102 y-101 =-0.82 Send data ol Regression line equation: -
6) Compute the least-squares regression line for predicting y from x given the following summary statistics. Round the slope and y -intercept to at least four decimal places. = x 8.8 = s x 1.2 = y 30.4 = s y 16 = r 0.60 Send data to Excel Regression line equation: = y 7)Compute the least-squares regression equation for the given data set. Use a TI- 84 calculator. Round the slope and y -intercept to at least four decimal...
SUMMARY OUTPUT Regression Statistics Multiple R 0.633614748 R Square 0.401467649 Adjusted R Square 0.388732918 Standard Error 7373785408 Observations ANOVA SS SS F Significance F 1 17141221.72 17141222 31.52541 1.02553E-06 4725555174.28 543727.1 48 4 2696396 1 17141221.72 17141222 3152541 Siewicowe Regression Residual Total Coefficients Standard Error Star P-value 2194.707265 332.0870736 6.608831 3.21E-08 40.870917 7279205668 5.61475 1.03E-06 Coefficients Standard Porn Photo Intercept Lower 95% Upper 95% Lower 95.096 Upper 95.0% 1526,634245 2862.780285 1526.634245 2862.780285 26.22704404 55.51478995 26.22704404 55.51478995 54 SUMMARY OUTPUT Regression...
Consider the following table summarizing the speed limit of a certain road and Type numbers in the the number of accidents occurring on that road in January. Part 1:10 points boxes. Posted Speed Limit 53 49 44 36 21 23 * Part 2: 10 points Part 3: 10 points Reported Number of Accidents 25 28 20 17 18 14 30 points 1) Find the slope of the regression line predicting the number of accidents from the posted speed limit.Round to...
correlation and regression 210 Statistics EXTRA CREDIT Correlation and Regression Formulas written Assignment 1. Follow the instructions below to calculate the correlation coefficient and least squares regression line for the data set below. Z 22,- The sample means and sample standard deviations for the two variables are listed below: X = 4 x = 2 3 =5 Sy = 1 The linear correlation coefficient is = 52. Calculate this correlation coefficient using the steps below: (a) First, complete the columns...
What is the SCL equation for your regression output? A D 1 SUMMARY OUTPUT 2 Regression Statistics L3 4 Multiple R 5 R Square 6 Adjusted R Square 7 Standard Error 8 Observations 0.147788325 0.021841389 0.004680712 0.112847351 59 10 11 12 Coefficients Standard Error P-value 0.015008141 0.043055201 0.965808003 t Stat 13 Intercept 14 S&P 500 HPR 0.000646179 0.490477908 0.434756954 1.128165755 0.263976201 15 A D 1 SUMMARY OUTPUT 2 Regression Statistics L3 4 Multiple R 5 R Square 6 Adjusted R...
Compute the least-squares regression line for predicting y from x given the following summary statistics. Round final answers to four decimal places, as needed. x = 12.9 x 2.241000 S y 15000 0.60 Download data Regression line equation:
Find the equation of the regression line for the given data. Then construct a scatter plot of the given x-values, if meaningful. The table below shows the heights (in feet) and the number of stories of Height, Stories, y data and draw the regression line. (The pair of variables have a signiicant correlation.) Then use the regression equation to predict the value of y for each of the sb. notable buildings in a city 775 53 619 47 519 46...