Antibiotics in Infancy and WeightA Canadian longitudinal study examines whether giving antibiotics in infancy increases the likelihood that the child will be overweightlater in life. The children were classified as having received antibiotics or not during the first year of life and then being overweight ornot at 9 years old. The study included 616 children, and the results are shown in the table below.Overweight | Not Overweight TotalAntibiotics144294438No Antibiotics37141178Total181435616Round your answers to three decimal places.(a) What proportion ofchildren in the study were givencibiotics duringfirst year of life?i(b) What proportion of all children in the study were classified as overweight at age 9?i(c) What proportion of those receiving antibiotics were classified as overweight at age 9?i(d) What proportion of those not receiving antibiotics were classified as overweight at age 9?i(e) If we use PA to denote the proportion from part (c) and Py to denote the proportion from part (d), calculate the difference inproportion being overweight, PA – PN, between those that were exposed to antibiotics and those that weren't.- PNi(f) What proportion of all children classified as overweight were given antibiotics during the first year of life?i1Azad MB, Bridgman SL, Becker AB, Kozyrskyj AL, "Infant antibiotic exposure and the development of childhood overweight andcentral adiposity", International Journal of Obesity (2014) 38, 1290-1298.

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Answered: Antibiotics in Infancy and Weight A…

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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Buckle up! - How does seat belt use vary with drivers' ethnic group? It is well known that location and gender (males are less likely to buckle up) are factors. Here is the data and the mosaic plot for a random sample of male drivers observed in Houston. Ethnic group of driver Belted Not Belted Total Black 277 99 376 Hispanic 373 164 537 White 197 62 259 Total 847 325 1172 Ethnicity Hispanic Black White Use of Seat Belt wearing a seat belt not wearing a seat belt
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A case-control study is conducted to assess the relationship between heavy alcohol use during the first trimester of pregnancy and miscarriage. Fifty women who suffered miscarriage are enrolled along with 50 who delivered full term. Each participant’s use of alcohol during pregnancy is ascertained. Heavy drinking is defined as 4 or more drinks on one occasion. The data are shown below. Miscarriage Delivered Full Term Heavy Alcohol Use 14 4 No Heavy Alcohol Use 36 46 Compute the odds of miscarriage among women with heavy alcohol use in pregnancy.
What is the normal hypothesis and alternative hypothesis?
Aspirin III: Decision and Conclusion Regarding the experiment in the data frame Aspirin from the abd package, the researchers wanted to know whether or not taking aspirin affects one's risk of developing cancer. Recall that they defined their parameters as follows: p1 = the proportion of ALL individuals who would develop cancer, if all of them were to take aspirin like the subjects in the Aspirin group did. p2 = the proportion of ALL individuals who would develop cancer, if all of them were to take a placebo, like the subjects in the placebo group did. They ran the code for a two-sided significance test and got the following results: ## ## ## Inferential Procedures for the Difference of Two Proportions p1-p2:## cancer grouped by treatment ## ## ## Descriptive Results:## ## yes n estimated.prop## Aspirin 1438 19934 0.07214## Placebo 1427 19942 0.07156## ## ## Inferential Results:## ## Estimate of p1-p2: 0.0005805 ## SE(p1.hat - p2.hat): 0.002586 ## ##…
A popular, nationwide standardized test taken by high-school juniors and Españ seniors may or may not measure academic potential, but we can nonetheless attempt to predict performance in college from performance on this test. We have chosen a random sample of students just finishing their first year of college, and for each student we've recorded her score on this standardized test (from 400 to 1600) and her grade point average (from o to 4) for her first year in college. The data are shown below, with x denoting the score on the standardized test andy denoting the first-year college grade point average. The least-squares regression line for these data is 1.1239+0.0015x. This line is shown in the scatter plot below. Standardized test score, .x 1360 1100 790 1280 890 Grade point average, y 3.77 2.28 2.35 2.91 2.64 2.22 3.18 3.34 2.36 3.30 3.02 2.88 860 1400 1510 1000 1250 1060 1210 1020 940 1510 Send data to calculator ✓ Send data to Excel 3.07 2.29 3.01 Grade point average, 34- 324 900…
Need C and D
C. Predicting Student Success STA believes there is a relationship between high school GPA (on a four-point scale) and college performance (as measured by GPA on a four-point scale). The following data were randomly selected from among students enrolling Fall 2020. HS GPA STA GPA Student 1 HS GPA STAGPA Student 21 2.9 2.5 3.6 3.4 2 3.4 3.1 3.0 22 3.4 4.0 1.7 3 3.1 23 2.9 2.9 1.7 3.0 3.2 3.3 4 24 3.5 5 3.4 25 4.0 3.6 3.6 3.0 26 3.6 3.8 3.2 3.9 3.1 27 8. 4.0 3.9 28 3.4 3.6 3.2 9. 3.0 3.0 29 3.7 10 2.9 2.0 3.0 30 4.0 3.3 4.0 3.2 11 3.3 31 12 3.6 3.8 32 3.7 3.2 3.4 3.0 13 3.7 3.9 33 14 3.8 3.6 34 2.5 2.0 15 2.5 2.5 35 2.9 2.9 3.7 2.2 16 2.9 2.5 36 3.8 17 2.8 2.1 37 2.9 18 3.8 1.7 3.5 38 3.6 3.5 3.6 19 3.7 39 3.6 20 3.9 3.0 40 3.1 3.6 How confident should St. Mary's be regarding the accuracy of their predictions? Why?
C. Predicting Student Success STA believes there is a relationship between high school GPA (on a four-point scale) and college performance (as measured by GPA on a four-point scale). The following data were randomly selected from among students enrolling Fall 2020. HS GPA STA GPA Student 1 HS GPA STAGPA Student 21 2.9 2.5 3.6 3.4 2 3.4 3.1 3.0 22 3.4 4.0 1.7 3 3.1 23 2.9 2.9 1.7 3.0 3.2 3.3 4 24 3.5 5 3.4 25 4.0 3.6 3.6 3.0 26 3.6 3.8 3.2 3.9 3.1 27 8. 4.0 3.9 28 3.4 3.6 3.2 9. 3.0 3.0 29 3.7 10 2.9 2.0 3.0 30 4.0 3.3 4.0 3.2 11 3.3 31 12 3.6 3.8 32 3.7 3.2 3.4 3.0 13 3.7 3.9 33 14 3.8 3.6 34 2.5 2.0 15 2.5 2.5 35 2.9 2.9 3.7 2.2 16 2.9 2.5 36 3.8 17 2.8 2.1 37 2.9 18 3.8 1.7 3.5 38 3.6 3.5 3.6 19 3.7 39 3.6 20 3.9 3.0 40 3.1 3.6 Is high school GPA a good predictor of STA GPA? Why? What STA GPA would you predict for a student with a high school GPA of 3.75? How you would make the prediction.
Data on grades of students who did and did not attend class regularly. What are the mean and median scores of those two groups of students? What do they suggest about the value of attending class? Attended class 241 243 246 249 250 252 254 254 255 256 261 262 263 264 264 264 265 267 267 270 271 272 273 276 276 277 278 278 280 281 282 284 288 288 290 291 291 292 293 294 296 296 297 298 310 320 321 328 Skipped class 188 195 195 225 228 232 233 237 239 240 250 256 256 256 261 264 264 268 270 270…
A research group is conducting an experiment to study the relationship between fitness levels and the number of hours spent exercising each week. Subjects are randomly selected and, after several fitness tests, are assigned a fitness score. The number of hours spent exercising per week is also recorded. Data for 15 subjects are given below. Subject Hours of Exercise per Week Fitness Score 1 1 3 2 1.5 4.7 3 1.75 6 4 2 5 5 2 6.5 6 4.5 14.2 7 2.5 13.5 8 3.25 15 9 3 13.4 10 3.75 14 11 3.5 10 12 4 10 13 2.5 12 14 5.25 14.5 15 5 15 Create a bar graph in MicrosoftÂ® ExcelÂ® using the data. Label the graph and include the source of the data. Construct an equation in two variables that models this relationship. This equation may be linear, polynomial, rational, square root, or variation? Is the equation an exact model or an approximate model of the relationship between the variables? Explain your reasoning. Use the equation to make a prediction of the likely value of the…

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