5.7 1-al2 ne ES 3S Alpha 0 5 84 ES = nu San aliacodomou 2. An investigator wants to estimate caffeine consumption in high school students. How man students would be required to estimate the proportion of students who consume coffee? Suppose we want the estimate to be within 2%ofthe true proportion with 95% confidence 2- 8. 1 Alpha 15 50A95)- (1-0.5)(19 E= n= 335 35 (153644) 32 oni su 3. A crossover trial is planned to evaluate the impact of an educational intervention program to reduce alcohol consumption in patients determined to be at risk for alcohol problems. The plan is to measure alcohol consumption (the number of drinks on a typical drinking day) before the

A researcher administers a treatment to a sample from a population with a mean of m=50. If the treatment is expected to increase scores and a one-tailed test is used to evaluate the treatment effect, the the null hypothesis states that m=40. True or false?

Suppose it was found that in a random sample of 200 individuals who were underweight (defined as having a BMI of under 18.5), 8 of them were hospitalized with COVID-19.  Of a corresponding group of 400 individuals who were classified as severely obese (defined as having a BMI of at least 45.0), 32 were hospitalized with COVID-19. (a)  If you wanted to test this null hypothesis at the 95% confidence level, what would be your critical z? (b) What is the standard error of the difference between proportions (to 4 decimal places)?

To evaluate the effect of a treatment, a sample ofn = 8 is obtained from a population with a mean of m =50, and the treatment is administered to the individuals in the sample. After treatment, the sample mean is found to be M = 55. Assuming that the sample variance is s2 =32, use a two-tailed hypothesis test with a = .05 to determine whether the treatment effect is significant and compute both Cohen’s d and r2 to measure effect size. Assuming that the sample variance is s2 = 72, repeat the test and compute both measures of effect size. Comparing your answers for parts a and b, how does the variability of the scores in the sample influence the outcome of a hypothesis test and measures of effect size?

To evaluate the effect of a treatment, a sample is obtained from a population with a mean of μ = 25, and the treatment is administered to the individuals in the sample. After treatment, the sample mean is found to be M= 27.4 with SS = 64. If the sample consists of 9 individuals, what is the t statistic, and are the data sufficient to conclude that the treatment has a significant effect using a two-tailed test with α = .05?

To evaluate the effect of a treatment, a sample of  n = 8 is obtained from a population with a mean of μ = 50, and the treatment is administered to the individuals in the sample. After treatment, the sample mean is found to be M = 55. Assuming that the sample variance is s^2 = 32 , use a two-tailed hypothesis test with α = .05 to determine whether the treatment effect is significant and compute both Cohen’s d and r^2 to measure effect size. Assuming that the sample variance is s^2 = 72 , repeat the test and compute both measures of effect size. Comparing your answers for parts a and b, how does the variability of the scores in the sample influence the outcome of a hypothesis test and measures of effect size?

Suppose we took a random sample of 200 students and ask if they preferred morning, evening, or night classes. a.If 76 students preferred morning classes what is the 95% CI for the proportion of students who prefer morning classes? b. Based on this confidence interval what would be the decision to the hypothesis: H0 = .3 vs Ha ≠ .3 using alpha = .05? c.How large a sample should be taken in order to estimate the proportion to within 2%, with 99% confidence?

Suppose that Randy is an analyst for the bicyling industry and wants to estimate the asking price of used entry-level road bikes advertised online in the southeastern part of the United States. He obtains a random sample of ?=13n=13 online advertisements of entry-level road bikes. He determines that the mean price for these 13 bikes is ?⎯⎯⎯=$681.87x¯=$681.87 and that the sample standard deviation is ?=$177.45s=$177.45. He uses this information to construct a 99% confidence interval for ?μ, the mean price of a used road bike. What is the lower limit of this confidence interval? Please give your answer to the nearest cent.

To evaluate the effect of a treatment, a sample of n = 8 is obtained from a population with a mean of μ = 40, and the treatment is administered to the individuals in the sample. After treatment, the sample mean is found to be M = 35.   If the sample variance is s2 = 32, are the data sufficient to conclude that the treatment has a significant effect using a two-tailed test with α = .05?   =    If the sample variance is s2 = 72, are the data suffi- cient to conclude that the treatment has a signifi- cant effect using a two-tailed test with α = .05?   =   Comparing your answer for parts a and b, how does the variability of the scores in the sample influence the outcome of a hypothesis test?   =

A survey at a certain university found that 21 out of a random sample of 350 students had over $6,000 in credit card debt with a 90% confidence level of 0.04 to 0.08 If we would like the margin of error to be within 0.01, how large should the sample size be? ( Use P=0.5 for a conservative estimate.)