You design a study to test the impact of power study programs statistics exam results. You choose 21 students randomly from a statistics class to participate in the study. You randomly assign each student to one of the power groups. Students are later tested with a statistics exam with the material covered in the power study programs. You plan to use an ANOVA to test the impact of each of the power study programs with exam results. Use an alpha level of .05. Report your computed F-ratio, critical region, and your conclusion to accept or reject the null hypothesis. Power Study #1 Power Study #2 Power Study #3 85 85 92 86 89 87 82 82 80 75 75 89 66 88 96 78 76 83 87 82 92 F ratio _____ Critical region _____ Accept/Reject Null _____

You design a study to test the impact of power study programs statistics exam results. You choose 21 students randomly from a statistics class to participate in the study. You randomly assign each student to one of the power groups. Students are later tested with a statistics exam with the material covered in the power study programs. You plan to use an ANOVA to test the impact of each of the power study programs with exam results. Use an alpha level of .05. Report your computed F-ratio, critical region, and your conclusion to accept or reject the null hypothesis. Power Study #1 Power Study #2 Power Study #3 85 85 92 86 89 87 82 82 80 75 75 89 66 88 96 78 76 83 87 82 92 F ratio ___ Critical region _ Accept/Reject Null ___

College Algebra

1st Edition

ISBN:9781938168383

Author:Jay Abramson

Publisher:Jay Abramson

Chapter9: Sequences, Probability And Counting Theory

Section9.7: Probability

Problem 3SE: What is an experiment?

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What is an experiment?
A psychologist would like to examine the effects of different testing methods on the final performance of college students. One group has regular quizzes, one group has three large exams, and the third group only has a final exam. At the end of the course, the psychologist interviews each student to get a measure of the student’s overall knowledge of the material. Do these data indicate any significant differences among the three methods? Test with α = .05. Include a source table for this ANOVA and state whether your F ratio is significant. Calculate the η2 value for this effect and Compute Tukey’s HSD to determine exactly which methods are significantly different.
To check a new analytical method, a chemist obtains a reference specimen of known concentration from the National Institute of Standards and Technology. She then makes 20 measurements of the concentration of this specimen with the new method and checks for bias by comparing the mean result with the known concentration. What is the response variable? And what best describe the setting of this experiment? Does it have a two independent sample design or a single sample design?
A researcher is interested in the impact of joining a weight loss program in the past 12 months on the individuals weight loss. The analysis was restricted to people aged 16 and older who answered yes to the question "During the past 12 months, have you tried to lose weight?" About 5% of the sample had joined a weight loss program in the past year. 1. Discuss follow-up analyses that could be done after Propensity score matching.
The human resources director of a large company recently asked her staff to conduct a study of the airline miles traveled by executives of the company during the most recent calendar year. The analyst assigned to the project randomly sampled 25 male executives and 25 female executives. Of particular interest to the HR director is whether males have greater variability in miles flown than females. The statistics available below were computed from the samples. Based on these data, what should the HR director conclude if an alpha level equal to 0.01 is used? LOADING... Click the icon to view the statistics about the number of miles flown. Males Females Mean Miles 73,262 66,888 St. Deviation Miles 2,568 1,539 Sample Size 25 25 Let sample 1 be males and sample 2 be females. What are the null and alternative hypotheses? A. H0: σ21=σ22 HA: σ21≠σ22 B. H0: σ21≤σ22 HA: σ21>σ22 C. H0: σ21≥σ22 HA:…
Tardigrades, or water bears, are a type of micro-animal famous for their resilience. In examining the effects of radiation on organisms, an expert claimed that the amount of gamma radiation needed to sterilize a colony of tardigrades no longer has a mean of 900 Gy (grays). (For comparison, humans cannot withstand more than 10 Gy .) A study was conducted on a sample of 27 randomly selected tardigrade colonies, finding that the amount of gamma radiation needed to sterilize a colony had a sample mean of 907 Gy , with a sample standard deviation of 17 Gy . Assume that the population of amounts of gamma radiation needed to sterilize a colony of tardigrades is approximately normally distributed. Complete the parts below to perform a hypothesis test to see if there is enough evidence, at the 0.05 level of significance, to support the claim that μ , the mean amount of gamma radiation needed to sterilize a colony of tardigrades, is not equal to 900…
Tardigrades, or water bears, are a type of micro-animal famous for their resilience. In examining the effects of radiation on organisms, an expert claimed that the amount of gamma radiation needed to sterilize a colony of tardigrades no longer has a mean of 900 Gy (grays). (For comparison, humans cannot withstand more than 10 Gy .) A study was conducted on a sample of 27 randomly selected tardigrade colonies, finding that the amount of gamma radiation needed to sterilize a colony had a sample mean of 907 Gy , with a sample standard deviation of 17 Gy . Assume that the population of amounts of gamma radiation needed to sterilize a colony of tardigrades is approximately normally distributed. Complete the parts below to perform a hypothesis test to see if there is enough evidence, at the 0.05 level of significance, to support the claim that μ , the mean amount of gamma radiation needed to sterilize a colony of tardigrades, is not equal to 900…
Researchers have noted a decline in cognitive functioning as people age (Bartus, 1990). However, the results from other research suggest that the antioxidants in foods such as blueberries may reduce and even reverse these age-related declines (Joseph et al., 1999). To examine this phenomenon, suppose that a researcher obtains a sample of n = 16 adults who are between the ages of 65 and 75. The researcher uses a standardized test to measure cognitive performance for each individual. The participants then begin a 2-month program in which they receive daily doses of a blueberry supplement. At the end of the 2-month period, the researcher again measures cognitive performance for each participant. The results show an average increase in performance of MD = 7.4 with SS = 1215. Does this result support the conclusion that the antioxidant supplement has a significant effect on cognitive performance? Use a two-tailed test with α = .05. Show your computations.
To help assess the health risks of second-hand smoke, the levels of cotinine (a metabolite of nicotine) were measured in mmol/l in the urine of seven subjects prior to exposure to second-hand smoke and shortly after a two-hour exposure to secondary cigarette smoke. Did the exposure significantly increase the cotinine level? What will be the appropriate statistical analysis to use in this problem? a. z-Test for Comparing Two Means from Independent Populations b. t-Test for Comparing Two Means when the Samples are Dependent c. z-test for comparing the difference between two proportions d. t-Test for Comparing Two Means from Independent Samples e. F-test in Comparing the Difference Between Two Variances