The image presents an investigation focused on the relative risk (RR) estimates related to consuming pizza and alcoholic beverages. The task is to interpret the data regarding these estimates.**Table Explanation:**1. **Effect of drinking without regard to eating pizza:** - Crude RR = 3.02. **Effect of drinking among those who ate pizza:** - RR = 3.03. **Effect of drinking among those who did not eat pizza:** - RR = 3.0**Possible Interpretations:**A. The effect of drinking is confounded by eating pizza.B. Drinking is not a risk factor.C. Drinking is a risk factor and the RR=3.0.D. None of the above answers are correct.The relative risk (RR) is consistently 3.0 across different conditions, suggesting that drinking has the same risk irrespective of pizza consumption.

Given data is Effect of drinking without regard to eating pizza effect of drinking among those…

Answered: 18. The investigation has also…

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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Consider the data below. Previous studies have shown that approximately 32% of women deliver prematurely without treatment. Is the proportion of women delivering prematurely significantly higher in the placebo group? Run the test at a 5% level of significance. Preterm Delivery Experimental Drug Standard Drug Placebo Yes 17 23 35 No 83 77 65
d. what decision can you make and what does that mean? e. what type of error could you be making and what does that mean f. report results in apa format
could you please help to answer this question? thank you
The table below summarizes baseline characteristics of patients participating in a clinical trial. a) Are there any statistically significant differences in baseline characteristics between treatment groups? Justify your answer. Characteristic Placebo (n = 125) Experimental ( n =125) P Mean (+ Sd. Age 54 + 4.5 53 + 4.9 0.7856 % Female 39% 52% 0.0289 % Less than High School Education 24% 22% 0.0986 % Completing High School 37% 36% % Completing Some College 39% 42% Mean (+ Sd. Systolic Blood Pressure 136 + 13.8 134 + 12.4 0.4736 Mean (+ Sd. Total Cholesterol 214 + 24.9 210 + 23.1 0.8954 % Current Smokers 17% 15% 0.5741 % with Diabetes 8% 3% 0.0438
Was there a statistical difference in blood glucose between groups at baseline? (Complete t-test for baseline blood glucose between control and glucose groups; interpret results to answer question)
The table below summarizes baseline characteristics of patients participating in a clinical trial. a) Are there any statistically significant differences in baseline characteristics between treatment groups? Justify your answer. Characteristic Placebo (n = 125) Experimental ( n =125) P Mean (+ SD) Age 54 + 4.5 53 + 4.9 0.7856 % Female 39% 52% 0.0889 % Less than High School Education 24% 22% 0.0386 % Completing High School 37% 36% % Completing Some College 39% 42% Mean (+ SD) Systolic Blood Pressure 136 + 13.8 134 + 12.4 0.4736 Mean (+ SD) Total Cholesterol 214 + 24.9 210 + 23.1 0.8954 % Current Smokers 17% 15% 0.0441 % with Diabetes 8% 3% 0.0938
The following table shows the results of a survey focused on alcohol use among teen girls. Is there a significant relationship between race and trying alcohol among teen girls? Assume race is the independent variable. Add appropriate percentages to the table. a. Write one sentence describing the pattern you see, using specific percentages. b. State the null and research hypotheses c. Calculate the appropriate test statistic. d. What is the critical value at which p<.05? e. What do you conclude?
(3) The table contains hypothetical data from a study that a bank conducted on the credit card balances of male and female credit card holders (credit cards owned by both men and women were left out of the study). Male Female Mean $3,550 $2,670 Median $2,175 $2,500 Std Dev $1,240 $825 a. What conclusions can we come to by comparing the medians of the males and females? b. What conclusions can we come to by comparing the standard deviations of the males and females? c. Notice that the mean and median of the males are fairly far apart while the mean and median of the females are not. What does this tell us about the credit card balances of the males vs the credit card balances of the females?
Which of the following research scenarios uses a two samples independent-measures t test? a. Examine the difference in self-esteem between student athletes and non-athletes. b. Evaluate the effectiveness of a pain reliever by measuring how much pain is reduced after taking the medication in a single group of people who rated pain, then took the drug and rated pain a second time. c. Test the effectiveness of a cholesterol medication by comparing cholesterol levels before and after the medication is administered to a single group. d. Calculating the z score for the highest X in the data set.
As a good experimenter, you have built a predictive model of the experimental data. The differences between the actual response data and the model data are termed: A. Confounded data B. Nested experiments C. Residuals D. Efficiency of estimators
2. Recovering from surgery: A new postsurgical treatment was compared with a stan- dard treatment. Seven subjects received the new treatment, while seven others (the controls) received the standard treatment. The recovery times, in days, are given below. Can you conclude that the mean recovery time for those receiving the new treatment is less than the mean for those receiving the standard treatment? Use the a = 0.05 level. Treatment: Control: H₁: 12 18 (a) List the null and alternate hypetheses. Ho : (c) List the P-value. 13 23 (d) Make the comparison. 15 24 19 30 20 32 (b) List the distribution, the test statistic, the calculator program, and all input and output variables. 21 35 We reject Ho / We do not reject Ho (circle one) (e) State the final conclusion in the wording of the problem. 24 39
Research indicates that there may be a relationship between caffeinated coffee consumption and risk of depression in women. Provided is data on the amount of caffeinated coffee consumed and whether the woman was diagnosed with clinical depression. Of interest is to see if there is evidence of an association between caffeinated coffee intake and clinical depression in women. What are the hypotheses? Caffeinated coffee Depression <1 cup/wk >=1 cup/day 2-3 cups/day 4+ cups/day Total Yes 670 1278 564 95 2607 No 11545 22573 11726 2288 48132 Total 12215 23851 12290 2383 50739 A. H0: H0 is not true and there is no association between caffeine intake and depression in women B. There is no association between caffeine intake and depression in women and H0 is not true C. Research indicates that there may be a relationship between caffeinated coffee consumption and risk of depression in women D. H0: There is an association between caffeine intake and…

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Effect of drinking without regard to eating pizza	effect of drinking among those who eat pizza	effect of drinking among those who did not eat pizza
Crude RR=3.0	RR=3.0	RR=3.0