The impact of a low-calorie diet on laboratory mice's longevity is being investigatedby a medical researcher. Twenty mice are split into two groups (E and F) by random.A typical diet is given to Group E, while Group F is given a diet that only contains70% as many calories as Group E's diet. The length of life (in days) of each mouseover the 36-month trial is documented. Table 2 provides the data that was obtained.The symbol of double star (**) signifies that the mouse was still alive at the end ofthe investigation.(a)(b)(c)Table 2: The length of life (in days) of each mouseGroup E 900 907 751 833 920 787 830 877 848 901Group F 1037 905 1023 988 1078 1011 ** 1063 898 1033State a suitable null and alternative hypotheses for the problem.At 5% significance level, test the hypotheses in part (a) by using an appropriatenonparametric test.Write your conclusion.

Given the data as Group E Group F 900 1037 907 905 751 1023 833 988 920 1078 787 1011…

Answered: The impact of a low-calorie diet on…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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The article cited in Exercise 4 also investigated the effects of the factors on glucose consumption (in g/L). A single measurement is provided for each combination of factors (in the article, there was some replication). The results are presented in the following table. Glucose Consumption 68.0 -1 -1 -1 -1 -1 77.5 -1 -1 98.0 1. 1. -1 98.0 -1 -1 74.0 -1 77.0 -1 97.0 98.0 Compute estimates of the main effects and the interactions. a. Is it possible to compute an error sum of squares? Explain. Are any of the interactions among the larger effects? If so, which ones? d. Assume that it is known from past experience that the additive model holds. Add the sums of squares for the interactions, and use that result in place of an error sum of squares to test the hypotheses that the main effects are equal to 0. Ъ. C.
Answer part a
Using the same anti-venom study, answer the following questions. A study was done on children (6 months to 18 years of age) who had (nonlethal) scorpion stings. Researchers wanted to know the effectiveness of a new anti-venonm. Each child was randomly assigned to receive a shot of the anti-venom or a placebo shot. Researchers recorded whether or not their condition improved over the next four hours. a. Identify the population for the study. b. Identify the sample for the study. (HINT: See #1) c. Was this an observational study or a controlled experiment? Explain how you know. d. Assuming the rest of the study was well-designed, use your answers to discuss whether it would be reasonable to conclude that the new anti-venom is effective at treating nonlethal scorpion stings in children. For the toolbar, press ALT+F10 (PC) or ALT+FN+F10 (Mac). TTTTParagraph Arial 3 (12pt) 三,三,T. 回i:公 E=E= = T T, U HTML CSS O Mashups
During a particularly dry growing season in a southern state, farmers noticed that there is a delicate balance between the number of seeds that are planted per square foot and the yield of the crop in pounds per square foot. The yields were the smallest when the number of seeds per square foot was either very small or very large. The data in the table show various numbers of seeds planted per square foot and yields (in pounds per square foot) for a sample of fields. A 2-column table with 15 rows. Column 1 is labeled number of seeds (per square foot) with entries 28, 75, 30, 43, 71, 35, 40, 59, 66, 79, 85, 81, 16, 33, 16. Column 2 is labeled yield (pounds per square foot) with entries 131, 171, 132, 166, 169, 150, 161, 183, 173, 161, 147, 157, 86, 145, 86. Which scatterplot represents the seed and yield data? A graph titled number of Seeds and Crop Yield has seeds (per square foot) on the x-axis, and yard (pounds per square foot) on the y-axis. The points curve up to a point, and…
Are America's top chief executive officers (CEOs) really worth all that money? One way to answer this question is to look at row B, the annual company percentage increase in revenue, versus row A, the CEO's annual percentage salary increase in that same company. Suppose that a random sample of companies yielded the following data: Do these data indicate that the population mean percentage difference in corporate revenue (row B) is different from the population mean percentage increase in CEO salary? Use a 1% level of significance. (A) Are the data statistically significant at level α? Will you reject or fail to reject the null hypothesis? Since the interval containing the P-values has values that are larger than the level of significance, the data are not statistically significant and so we fail to reject the null hypothesis. (a)Since the interval containing the P-values has values that are larger than the level of significance, the data…
Assume that the following data came from a case-control study. CasesControlsExposed4050Unexposed60150Based on this table, what proportion of exposed cases would have been eliminated if the cases had not been exposed (assuming that the exposure does contribute to the disease). 50% 100% 0% 33.3%.
A researcher uses an anonymous survey to track the number of salmon caught in Gaspe. Based on a set of 115 surveys distributed to a select few of the many hundreds of anglers who fished Gaspe, it was determined that anglers caught an average of 2.3 salmon per week. For this study, the average of 2.3 salmon per week is an example of which one statistic parameter. population sample
Suppose we are interested in comparing the proportion of male students who smoke to the proportion of female students who smoke. We have a random sample of 150 students (60 males and 90 females) that includes two variables: Smoke = "yes" or "no" and Gender = "female (F)" or "male (M)". The two-way table below summarizes the results. Smoke = Yes Smoke = No Sample Size 60 90 Gender = M Gender = F Reference: 3-15-No Tech 9 9 51 81 Describe how to use the data to construct a bootstrap distribution. What value should be recorded for each of the bootstrap samples.
2. Two-factor ANOVA - Emphasis on calculations W. Thomas Boyce, a professor and pediatrician at the University of British Columbia, Vancouver, has studied interactions between individual differences in physiology and differences in experience in determining health and well-being. Dr. Boyce found that some children are more sensitive to their environments. They do exceptionally well when the environment is supportive but are much more likely to have mental and physical health problems when the environment has challenges. You decide to do a similar study, conducting a factorial experiment to test the effectiveness of one environmental factor and one physiological factor on a physical health outcome. As the environmental factor, you choose two levels of oral hygiene. As the physiological factor, you choose three levels of cortisol value. The outcome is number of cavities, and the research participants are kindergartners. You conduct a two-factor ANOVA on the data. The two-factor ANOVA…
Identify whether the studies described here are based on (1) single samples, (2) paired samples, or (3) independent samples. Cardiovascular disease risk factors are compared in husbands and wives. A nutritional exam is applied to a random sample of individuals. Results are compared to the results of the whole nation. An investigator compares vaccination histories in 30 autistic schoolchildren to a simple random sample of non-autistic children from the same school district.
The Wisconsin Fish and Game Department stocked a lake with 30% catfish, 15 % bass, 40% bluegill, and 15% Northern Pike. Five years later they took a random sample of 500 fish from the lake and found 120 catfish, 85 bass, 220 bluegill, and 75 Northern Pike. At the 5% level of significance, can we show that the distribution of fish changed over the 5-year interval? State and test appropriate hypotheses. State conclusions.
Your statistics instructor often ponders the relationship between commute time and job satisfaction while driving back and forth to campus. Your instructor hypothesizes that people with a shorter commute time will have higher degrees of job satisfaction. Randomly sampling 600 Valley commuters, the instructor finds the following data listed in frequencies: Table 2: Commuters by Length of Commute and Job Satisfaction Job Satisfaction Number Who Commute 20 Minutes or Less Number Who Commute 21 to 40 Minutes Number Who Commute 41 Minutes or More Total Number for Each Level of Job Satisfaction Dissatisfied 10 60 140 210 Neutral 45 59 51 155 Satisfied 145 60 30 235 Total Number for Each Commute Time Range 200 179 221 1. Change frequencies to column percentages.

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