If the slope of the regression line is calculated to be 3.23 and the y' intercept is 18.18 then the approximated value of y when x is 5 is
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- If I add the additional condition which is the labor is female using the following: #People who is femalefemale = x*0.46 Will it become dependent variable and how will I do linear regression model by adding this condition?The following table gives the data for the grades on the midterm exam and the grades on the final exam. Determine the equation of the regression line, yˆ=b0+b1x�^=�0+�1�. Round the slope and y-intercept to the nearest thousandth. Grades on Midterm and Final Exams Grades on Midterm 7171 6262 7878 9494 8383 8181 8080 9494 8585 6262 Grades on Final 8888 7979 8888 9191 8080 7070 7171 9393 6565 7777The following table gives the data for the grades on the midterm exam and the grades on the final exam. Determine the equation of the regression line, yˆ=b0+b1xy^=b0+b1x. Round the slope and y-intercept to the nearest thousandth. Grades on Midterm and Final Exams Grades on Midterm 78 63 85 92 82 89 69 89 83 61 Grades on Final 77 75 88 92 86 86 80 85 77 63
- A value of r close to plus or minus 1 indicates that there is a strong linear relationship between the variables true or false?The accompanying data are the number of wins and the earned run averages (mean number of earned runs allowed per nine innings pitched) for eight baseball pitchers in a recent season. Find the equation of the regression line. Then construct a scatter plot of the data and draw the regression line. Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. If the x-value is not meaningful to predict the value of y, explain why not. (a) x= 5 wins E Click the icon to view the table of numbers of wins and earned run average. (b) x = 10 wins (c) x = 19 wins (d) x= 15 wins ..... The equation of the regression line is y = x+O (Round to two decimal places as needed.) Wins and ERA Earned run Wins, x average, y 20 2.71 18 3.19 17 2.69 16 3.68 14 3.94 12 4.25 11 3.86 9 5.18 Print Donealso compute the regression equation in which you predict Y using X as the predictor variable
- The accompanying data are the number of wins and the earned run averages (mean number of earned runs allowed per nine innings pitched) for eight baseball pitchers in a recent season. Find the equation of the regression line. Then construct a scatter plot of the data and draw the regression line. Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. If the x-value is not meaningful to predict the value of y, explain why not. (a) x = 5 wins Click the icon to view the table of numbers of wins and earned run average. (b) x = 10 wins (c) x = 21 wins (d) x = 15 wins ERA 6- ERA 6- AERA 6- ERA 6- 4- 4- 4- 4- 2- 2- 2- 2- 0+ 6 0- 0- 0- 12 18 24 6. 12 18 24 12 18 24 6 12 18 24 Wins Wins Wins Wins (a) Predict the ERA for 5 wins, if it is meaningful. Select the correct choice below and, if necessary, fill in the answer box within your choice. A. ŷ= (Round to two decimal places as needed.) B. It is not meaningful to predict this value of y because…The relationship between the entrance exam score (x) of MBA students and their GPA (y) upon graduation is given by ŷ = -0. 57 +0. 013x Based on this model, the predicted GPA of a student who had 200 for the entrance exam score is (Keep 2 decimal places) and the value of the slope of this fitted regression line is (Keep all the decimal places)A researcher knows that people with higher annual salaries commit fewer crimes. He is creating a regression model to predict the number of crimes a person will commit based on their salary Based on this information alone which of the following MUST be the slope of the regression line choose one 1.00 or 0.50 or -0.50
- Step 9 (d) What proportion of the observed variation in efficiency ratio can be attributed to the simple linear regression relationship between the two variables? The proportion of the observed variation in efficiency ratio which can be attributed to the simple linear regression relationship is equal to the coefficient of determination, r². r² = 1- SSE SST' where SSE = Syy - B₁Sxy, and SST = Syy. First, use v² = 77.1001, (v₁)² = (40.17)² = 1,613.6289, and n = 24 to calculate Sy yy' Swy = y? - = 77.1001 n Since SST = S, 1,613.6289 24 Syy, it follows that SST = Submit Skip (you cannot come back) rounded to six decimal places.Data was collected for a regression analysis where sleep quality (as a percentage) depends on the amount of caffeine consumed in a day (measured in mg). bo was found to be 92.7, bị was found to be -0.76, and R' was found to be 0.86. Interpret the slope of the line. On average, each one mg increase in caffeine consumed increases a person's sleep quality by 92.7%. On average, when x = 0, a person has a sleep quality of -0.76%. On average, when x = 0, a person has a sleep quality of 92.7%. On average, each one mg increase in caffeine consumed decreases a person's sleep quality by 0.76%. We should not interpret the slope in this problem. We should interpret the slope in this problem, but none of the above are correct.The regression line for the given data is = 6.91x + 46.26. Determine the residual of a data point for which x = 4 and y = 75.