Question 2A drug company wishes to compare the effects of three different drugs (X, Y, and Z) that arebeing developed to reduce cholesterol levels. Each drug is administered to six patients at therecommended dosage for six months. At the end of this period the reduction in cholesterol levelis recorded for each patient. The results are given in Table 12.14. Using these data we obtainSSTO= 2547.8, SSE = 395.7, xx = 23.67, xy = 39.17, and x₂ = 12.50. Completely analyzethese data using one-way ANOVA. DS CholRedTABLE 12.14Reduction ofCholesterol LevelsDS CholRedDrugXY224031351947274125391833NFSHINSZ1591411215

Null Hypothesis: H0: There is no difference in the effects of the three different drugs. Alternative…

Answered: A drug company wishes to compare the…

Linear Algebra: A Modern Introduction

4th Edition

ISBN:9781285463247

Author:David Poole

Publisher:David Poole

Chapter7: Distance And Approximation

Section7.3: Least Squares Approximation

Problem 31EQ

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Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?
Question # 1 A well-known multinational FMCG produces more than fifty products and sells them in the market. Out of fifty products one is mineral water for drinking purpose and supplies different size pack bottles in the market. Product manager observed that, during hot days the sale of water is more as compared to the normal days. He started the collection of data of weekly sale of water and the average weekly temperature. Product manager was interested in developing a relationship between sales and temperature; therefore, he discussed and shared the following data with you. sales 75 77 69 63 79 80 77 70 73 87 72 73 80 80 69 84 77 72 74 81 temperature 32 36 31 31 34 29 32 35 28 31 30 31 29 35 36 28 32 33 32 33 Sale is in thousand liters and temperature is in degree Celsius. Data…
Question 7 Consider a cohort study to compare the mortality rate of myocardial infarction (MI) in men with sedentary work (exposed group) to men with physically active work (unexposed). If in the exposed, there were 36,000 person (man) years of observation and 126 deaths whereas the unexposed had 24,000 man-years of observation and 44 deaths. Compute the following a) Mortality rate in each cohort? b) What is the relative risk of dying, comparing these 2 groups? c) What is the attributable risk of sedentary work? d) What is the attributable benefit of physical activity? e) If we assume that MI is associated with the mortality in this cohort (causality), what proportion of the disease in the higher group is potentially preventable?
QUESTION 3 The Research Unit for Cecilion Supermart conducted an experiment to estimate the strength of thecarrier bag from the starch-based biofilms made from two different jicamas (sengkuang) of type Aand type B. However, the researcher claims that jicama type A produces more strength comparedto type B. To support this claim, 10kg weight item was put into 100 carrier bags made from jicamatype A and 200 carrier bags made from jicama type B were randomly selected. As a result, 8 bagsfrom jicama type A burst while 12 bags from jicama type B burst. Calculate a 95% confidenceinterval for the difference in true proportion of the carrier bags which burst between jicama type Aand type B. Give comment on the parameter estimate.
Consider the following variables: Y=daily productivity score (measured in points) X1=0 if undergraduate student,1 if graduate student X2=hours of sleep per night 1. The plot shown below could possibly be the graph of which model? 2. If you want to test whether type of student modifies the association between hours of sleep per night and daily productivity score, which model should you consider and what is the null hypothesis for this test? 3. Suppose you use Model 5 to describe the relationship between type of student, hours of sleep per night, and daily productivity score. You use the method of least squares to obtain: Y = -0.5 + 3 (X1) + 1.5 (X2) + 2.5 (X1)(X2).
Cell Phone Radiation Listed below are the measured radiation absorption rates (in W/kg) corresponding to these cell phones: iPhone 5S, BlackBerry Z30, Sanyo Vero, Optimus V, Droid Razr, Nokia N97, Samsung Vibrant, Sony Z750a, Kyocera Kona, LG G2, and Virgin Mobile Supreme. The data are from the Federal Communications Commission. If one of each model of cell phone is measured for radiation and the results are used to find the measures of variation, are the results typical of the population of cell phones that are in use?

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