Which of the following is used to illustrate the “best guess” as to the predicted Y variable score based on X? Group of answer choices regression line standard error of the estimate scatter plot F equation
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- Which of the following statements is true? 1. The R (ie., R-squared) tells us the percentage of the variation in the dependent variable (cost) that is explained by variation in the independent variable (activity) II The R (e. R-squared) varies from 0% to 100%, and the lower the percentage, the better the fit of the data to a straight line. ONeither statement is true. Only statement I is true. Only statement II is tru. Both statements are true.need the correct solves asap plzWhat is the null hypothesis to test the significance of the slope in a regression equation? Multiple Choice Ho:B 20 Ho: Bs0 O Ho: B = 0 Ho: B 0
- The 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 40 inches. Is the result close to the actual weight of 352 pounds? Use a significance level of 0.05. Chest size (inches) *Weight (pounds) 44 54 328 528 41 55 39 51 418 580 296 503 Click the icon to view the critical values of the Pearson correlation coefficient r. - What is the regression equation? x (Round to one decimal place as needed.)The 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 12Statistical technique used to determine the degree to which two variables are related is known as a. Regression b. Correlation c. None of these d. Dispersion
- Ocean currents are important in studies of climate change, as well as ecology studies of dispersal of plankton. Drift bottles are used to study ocean currents in the Pacific near Hawaii, the Solomon Islands, New Guinea, and other islands. Let x represent the number of days to recovery of a drift bottle after release and y represent The distance from point of release to point of recovery in km/100. The following data a representative of one study using drift bottles to study ocean currents. x day 72 79 32 96 203 y km/100 14.8 19.6 5.3 11.8 35.1 Σx=482 Σy=86.6 Σx2=62874 Σy2=2002.54 Σxy=11041.7 r=.93787 use a 1% level of significance to test the claim p>0.(use 2 decimal places) t=critical t= Se=4.4913 a=1.4966 b=.1641 D) find the predicted distance (km/100) when a drift bottle has been floating for 80 days.(use 2 decimal places) find a 90% confidence interval for your prediction of part D. (use 2 decimal places) lower limit=___km/100upper limit=___km/100 he was a 1% level of…Which of the following denotes the slope or the regression coefficient for X? A) The term a B) The term b C) The error term D) The correlation coefficient, rQuestion. Using the following regression result, make your answers to the questions. Call: Im(formula - wage - educ, data - data) Residuals: 10 Median -5.1579 -2.5066 0.3816 2.4539 4.4737 Min 30 Max Coefficients: Estimate Std. Error t value Pr(>1tl) (Intercept) 9.0526 educ 5.1420 1.761 0.11635 2.1842 0.5994 3.644 0.00655 ** --- Signif. codes: 0 ***** 0.001 *** 0.01 ** 0.05 . 0.1' 1 Residual standard error: 3.305 on 8 degrees of freedom Multiple R-squared: 0.6241, F-statistic: 13.28 on 1 and 8 DF, p-value: 0.006549 Adjusted R-squared: 0.5771 1) Using the estimate and standard error of educ variable, perform the following hypothesis test. Ho:Beduc = 0 H1: Beduc # 0 2) Interpret the above hypothesis test result.
- Using data from 50 workers, a researcher estimates Wage Be + B₁Education + B2Experience + B3Age +, where Wage is the hourly wage rate and Education, Experience, and Age are the years of higher education, the years of experience, and the age of the worker, respectively. A portion of the regression results is shown in the following table. Coefficients Standard Error t Stat p-Value Intercept 7.45 3.79 1.97 0.0554 Education 1.06 0.37 2.86 0.0063 Experience 0.37 0.18 2.06 0.0455 Age -0.02 0.06 -0.33 0.7404 a-1. Interpret the point estimate for ẞ1. As Education increases by 1 year, Wage is predicted to increase by 1.06/hour. As Education increases by 1 year, Wage is predicted to increase by 0.37/hour. As Education increases by 1 year, Wage is predicted to increase by 1.06/hour, holding Age and Experience constant. As Education increases by 1 year, Wage is predicted to increase by 0.37/hour, holding Age and Experience constant. a-2. Interpret the point estimate for ẞ2. ○ As Experience…Identify the variable as either qualitative or quantitative.(a) months in the year (b) distance of a successful field goal during a football seasonThe data show the bug chirps per minute at different temperatures. Find the regression equation, letting the first variable be the independent (x) variable. Find the best predicted temperature for a time when a bug is chirping at the rate of 3000 chirps per minute. Use a significance level of 0.05. What is wrong with this predicted value? Chirps in 1 min 1118 796 1161 918 1103 1219 Temperature (F) 82 72.2 92.2 73 87.5 94.4
