Question

the questions for the table for number 14 was added

For questions 13-16: Light exposure in mice Studies show that night-time light exposure is hamful to human health. A recent 6-week study randomly assigned lab mice to one of three conditions: LD (Group 1) had a standard light/dark cycle cach 24-hour period; (Group 2) LL had bright light all the time, and (Group 3) DM had dim light when there nomally would have been darkness. The rescarchers hoped to investigate how light exposure interacts with eating and sleeping cycles and whether it has an effect on weight gain. Among the variables recorded was the amount of body mass gained (g) by cach mouse over the 6-week period. Below are the results of the study. Sample size Mean Standard Deviation Group 7.859 3.009 1: LL 10 5.926 2: LD 1.899 2: DM 1,010 2.624 13. The researchers behind the study wish to conduct an ANOVA procedure to assess whether they can conclude the mean gain in body mass among the three groups of mice is significantly different. Which of the following is the appropriate set of hypotheses to test? Choose one. A) Hoi = B) H -i vs Hi At least one , is different from others C) Hai - D) None of these is corect. Hais vs Hai At least one , is different from others vs 14. Complete the ANOVA table (see the answer sheet) by filling in the blank cells 15. Compute the p-value associated with the F-test statistic in (14) 16. Use the results of your ANOVA procedure in (14) to select the appropriate conclusion regarding the null hypothesis for this research scenario. A) Reject Ho. We have sufficient evidence to say at least one of the three treatments corresponds to a mean weight gain (g) different than the others. The observed differences are not due to chance B) Reject Ho We have insufficient evidence to say at least one of the three treatments corresponds to a mean weight gain (g) different than the others. The observed differences are due to chance. C) Fail to reject Ho. We have insufficient evidence to say at least one of the three treatments corresponds to a mean weight gain (g) different than the others. The observed differences are due to chance. D) Fail to reject He. We have sufficient evidence to say at least one of the three treatments corresponds to a mean weight gain (g) different than the others. The observed differences are not due to chance. 14. Complete the ANOVA table below by filling in the blank cells that are not greyed out. Refer to the question about Light exposure in mice Degrees of Sum of Squares Mean square Source F-ratio Freedom Light Error 161.84 Total 274.92 For questions 17-20: Match the corelation coefficient to the scatter plot. Choose from the following values, using each only once: Use the "best" values that match the scatterplot 1.25, 0.95, 0.75, 0.52 0.08, -0.56, 0.76. -0.99 18 19 20 21. A sample of size n-27 is used to conduct a significance test for H -75 versus H 75. The test statistic is -3.45. What are the degrees of freedom for this test statistic? A) 26 B) 27 74 D) 75 Use the following for Question 22 & 23: A simple random sample of eight drivers was selected. All eight drivers are insured with the same insurance company, and all have similar auto insurance policies. The following table lists their driving experiences (in years) and monthly auto insurance premiums. Driving experience (years) Monthly auto insurance premium (S) 5 2 12 64 77 50 71 44 56 42 60 15 6 25 16 22. What is the equation of the least square regression line? Round your answer to one decimal 23. Predict the monthly auto insurance premium for a driver with 10 years of driving experience For Questions 24-26: Baby Birth Weight The Child Health and Devellopment Studies considered pregnancies among women in the San Francisco East Bay area. Rescarchers took a random sample of 100 pregnancies and used statistical software to construct a linear regression model to predict a baby's birth weight in ounces from the length of gestation (the number of days the mother was pregnant). A portion of the computer output is shown below. Coefficients: Prt 0.479 1.93e-05 Estimate 22.1960 0,5065 Std. Eror 31.2559 0.1127 t-value 0.710 4.492 (Intercept) gestation Residual standard eror: 16.93 on 98 degrees of freedom Multiple R-squared: 0.1708, Adjusted R-squared: 0.1623 24. What is the correlation between x gestation length and y birth weight? C) 0.0292 A) 0.1708 B) 16.93 E)-0.4133 D) 0.4133 A baby in the data set had a gestation length of 260 and a birth weight of 84 ounces. Compute the weight of the baby predicted by the model along with its corresponding residual. 25. Predicted value is 26. Residual is

Answer 1

As HOMEWORKLIB RULES rule , i will answer 3 separate questions only .

please send the reaming question separately , i will answer it .

thank you!