Given the regression line Ý = 2.5X +12, what is the predicted value of self-esteem where X = 5? O 14 O 12.5 O 24.5 22
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- o pis pe Suppose a doctor measures the height, x, and head circumference, y. of 11 children and obtains the data below. The correlation coefficient is 0.899 and the least squares regression line is y = 0.185x+ 12.276. Complete parts (a) and (b) below. Height, x Head Circumference, y 17.4 17.1 17.2 16.9 17.4 17.1 17.1 17.3 17.3 17.3 17.4 27.75 25.75 26.75 25.75 28 26.5 25.75 26.75 27 27.25 27.25 (a) Compute the coefficient of determination, R?. R2 = % (Round to one decimal place as needed) (b) Interpret the coefficient of determination k Approximately % of the variation in (Round to one decimal place as needed.) is explained by the least-squares regression model. Enter your answer in each of the answer boxes. Save for Later DUE RTTT:DY PIVT Score: o:5SYO Tor Tv attempts 3:35 PA- a 2/22/202 Type here to search insert prt sc 4+ backsp %23 6. 8.I’m taking a statistics and probability class. Please get this correct because I want to learn. I have gotten wrong answers on here beforeSuppose that a regression line is found to be ý = 0.5470x +7.7000 What is the predicted value for a = 7? O a. 11.53 O b. 54-45 C. 53-35 O d. -3.87
- Provide a detailed interpretation analysis of the regression results below. Pay attention to the main tested variables, model fit characteristics (R 2 ) and number of respondents in the sample. State what is dependent and what are independent variables. Was the hypotheses rejected or confirmed? a) H1: If a woman has a job she will have less children born b) H2: The younger a woman got married the more children she has c) H3: Education positively affects number of children to haveThe following data gives the number of employees at the bookstore and the number of minutes students wait in line to buy books at the beginning of the term. The independent variable is the number of employees and the dependent variable is the number of minutes. What is the y intercept? SSxx = 56.857; SS=2095.714; SSxy=-322.571 SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square XA356899 0.96 0.93 0.91 y 67 54 47 33 31 25 12The data from the table below gives a regression that is a) reliable. b) unreliable. c) unable to determine the reliability.
- Please answer... I'm needed only 1 hours time to dd .... Thank uExercise 6. Regression Fallacy. Historically, scores on the two midterms had a correlation of 0.48. Suppose that Jeri scored 2.1 standard deviations below the mean on the first midterm. (a) How many standard deviations [above or below?] the mean would you predict for her second midterm?Run a regression analysis on the following data set with y as the response variable. y 114 67.1 40.3 87.2 89 91.4 26.5 92.3 9.8 94.9 22.2 88.3 -0.5 What is the predicted value of the response variable when x = 82.5? y= || Round to 1 decimal place. xin
- The statistic used to test whether individual regression coefficients are different from zero in the population is: Select one: a. F O b. b Oc. R2 O d. t Clear my choicePlease assist second part? Thank you!11. For temperature (x) and number of ice cream cones sold per hour (y). (65, 8), (70, 10), (75, 11), (80,13), (85, 12), (90, 16). Interpret the coefficient of determination. Optional Answers: 1. 88.2% of the variability in the number of cones sold is explained by the least-squares regression model. 2. 93.9% of the variability in the number of cones sold is explained by the least-squares regression model. 3. 88.2% of the variability in the temperature is explained by the least-squares regression model. 4. 93.9% of the variability in the temperature is explained by the least-squares regression model.
