Compute the correlation coefficient between radiation dose and exposure time.
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- A student is interested in knowing if there is a relationship between the age of a child and the amount of time spent on homework. He asks 7 people their ages and the number of hours they spend on homework. Is there a relationship between age and the amount of time spent doing homework? Test at α = .05 level of significance. Age of Child (yrs) Time doing HW (hrs) 11 5 15 7 4 0 7 1 9 2 5 0 13 3Suppose that there is a correlation of r = 0.41 between the amount of time that each student reports studying for an exam and the student's grade on the exam. This correlation would mean that there is a tendency for people who study more to get better grades. Question 21 options: True FalseA special education teacher did research on whether or not there is a relationship between the number of students in his class and the number incidents of “acting out” behaviors exhibited by the autistic students in the classroom. He collects data for a year and aggregates them by month. He obtained the statistics below, r= -.863 R2=.74 b= -1.212294 a= 131.176598 10.) How does the presence of more students affect the incidents in the class? a) as students are added the incidences increase b) as students are added the incidences decrease c) the number of students does not affect acting out d) the number of students caused more incidents How much of the variability of acting out is explained by the number of students in the class?___________
- An article in Air and Waste ("Update on Ozone Trends in California's South Coast Air Basin," Vol. 43, 1993) studied the ozone levels on the South Coast air basin of California for the years 1976-1991. The author believes that the number of days that the ozone exceeds 0.20 parts per million depends on the seasonal meteorological index (the seasonal average 850 millibar temperature). The data follow: Year Days Index 16.3 1976 91 1977 105 17.1 1978 106 18.2 1979 108 18.1 1980 88 17.2 1981 91 18.2 1982 58 16.0 1983 82 17.2 Round your answers to 2 decimal places. (a) Fit a simple linear regression model to the data. Test for significance of regression using a = 0.05. y = i Calculate fo: i Year Days Index 1984 82 17.7 1985 65 17.2 1986 61 16.9 1987 48 17.1 1988 61 18.2 1989 43 17.3 1990 33 17.5 1991 36 16.6 i + i Is the simple linear regression model significant? No. (b) Calculate a 95% confidence interval on the slope. ≤B₁ ≤i XA paper gives data on x = change in Body Mass Index (BMI, in kilograms/meter2) and y = change in a measure of depression for patients suffering from depression who participated in a pulmonary rehabilitation program. The table below contains a subset of the data given in the paper and are approximate values read from a scatterplot in the paper. BMI Change (kg/m²) Depression Score Change S = The accompanying computer output is from Minitab. Depression score change 15- 10- -0.5 S Fitted Line Plot Depression score change = 6.577 +5.440 BMI change 20- 5.30586 Coefficients T 0.0 0.5 -0.5 R-sq 25.96% - 1 Term Coef Constant 6.577 BMI change 5.440 % 0.5 BMI change 1.0 SE Coef 2.28 2.90 9 0 0.1 0.7 0.8 1 1.5 4 T-Value 2.88 1.87 Interpret this estimate. s is the typical amount by which the ---Select--- line. 4 5 Regression Equation Depression score change = 6.577 +5.440 BMI change P-Value 0.0164 0.0906 S 5.30586 25.96% R-Sq R-Sq (adj) 18.56% 8 (b) Give a point estimate of o. (Round your answer to…A researcher is interested in testing the relationship between smoking and BMI (kg/m2) in adults aged 30-45. In order to test this association, the researcher divides smoking into currently more than a pack a day, currently less than a pack a day, and never smokers. The following table represents the BMIs for each participant enrolled by their respective smoking category. Current Smoker (≥1pack/day) Current Smoker (<1 pack/day Never Smoked 26.7 29.4 22.1 29.4 28.6 30.4 24.3 27.4 21.3 28.4 23.2 26.4 21.6 20.1 19.7 27.4 20.6 19.8 26.8 19.7 21.6 36.4 19.6 22.3 31.5 21.6 24.3 27.4 21.5 *Continue as though all assumptions for ANOVA are met. A) Calculate the MSW and MSB for the data represented above. B) Carry out a formal test for a one-way analysis of variance among the groups and interpret your results.
- Cardiovascular Disease Suppose the incidence rate of myocardial infarction (MI) was 5 per 1000 among 45- to 54-year-old men in 2000. To look at changes in incidence over time, 5000 men in this age group were followed for 1 year starting in 2010. Fifteen new cases of MI were found. Suppose that 25% of patients with Mi in 2000 died within 24 hours. This propartion is called the 24-hour case-fatality rate. Of the 15 new MI cases in the preceding study. 5 died within 24 hours. Test whether the 24-hour case- fatality rate changed from 2000 to 2010.11.8 Fast-food. If you go to the website for any fast-food chain, you can generally find information about the nutritional content of menu items. In February 2019, a sample of 130 menu items was selected from 13 popular fast-food chains, and the amount of carbohydrates (measured in grams) was recorded for each of these items. Figure 11.10 shows the distribution of grams of carbohydrates from the 130 menu items. Describe the shape, center, and variability of this distribution. Are there any outliers? 40 30 20 10 20 40 60 80 100 120 140 Total carbohydrates (in grams) Moore/Notz, Statistics: Concepts and Controversies, 1Oe, © 2020 W. H. Freeman and Company FrequencyLecture(8.8): The amount of time people engage in physical activity mat be related to health outcome. Those who report that they spend more than 15 hours are put into one while those who spend less 10 were put into another group. (Those who fall in between 10 and 15 were left out of the study); The reaearcher then ask the participants to wear a monitor for one month. The average time in minutes is recorded and shown below . Is there any evidence that on average people who watch less than 10 hours watching televsion spend more time on physical activity.?. Test the hypotheses at (alpha=0.05) using the 5 step procedure <10 hours 75 63 118 35 82 >15 hours 62 6 78 43 22 33