What is your conclusion using a one sided z test if you assume α=0.01 and test the hypothesis that the proportion of colic is less among infants of mothers who don’t smoke than among the infants of mothers who smoke?
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What is your conclusion using a one sided z test if you assume α=0.01 and test the hypothesis that the proportion of colic is less among infants of mothers who don’t smoke than among the infants of mothers who smoke?
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- Participants in a study of a new medicatioEyeglassomatic manufactures eyeglasses for different retailers. They test to see how many defective lenses they made in a given time period and found that 10% of all lenses had defects of some type. Looking at the type of defects, they found in a three-month time period that out of 34,024 defective lenses, 5840 were due to scratches. Are there more defects from scratches than from all other causes? State the Type I and Type II errors in this case.State the Type I error. Concluding that the proportion of defects from scratches is 10%, when in reality it is less than 10%. Concluding that the proportion of defects from scratches is 10%, when in reality it is higher than 10%. Concluding that the proportion of defects from scratches is less than 10%, when the proportion is actually 10%. Concluding that the proportion of defects from scratches is higher than 10%, when the proportion is actually 10%. State the Type II error. Concluding that the proportion of defects from scratches is…Alt 3. Highway Accidents: DUI the U.S. Department of Transportation, National Highway Traffic Safety Administration, reported that 77% of all fatally injured automobile drivers were intoxicated. A random sample of 27 records of automobile driver fatalities in Kit Carson County, Colorado, showed that 15 involved an intoxicated driver. Do these data indicate that the population proportion of driver fatalities related to alcohol is less than 77% in Kit Carson County? Use a = 0.01.
- Eyeglassomatic manufactures eyeglasses for different retailers. They test to see how many defective lenses they made in a given time period and found that 12% of all lenses had defects of some type. Looking at the type of defects, they found in a three-month time period that out of 34,544 defective lenses, 5865 were due to scratches. Are there more defects from scratches than from all other causes? State the Type I and Type II errors in this case. State the Type I error. Concluding that the proportion of defects from scratches is higher than 12%, when the proportion is actually 12%. O Concluding that the proportion of defects from scratches is 12%, when in reality it is less than 12%. Concluding that the proportion of defects from scratches is 12%, when in reality it is higher than 12%. O Concluding that the proportion of defects from scratches is less than 12%, when the proportion is actually 12%. State the Type II error. Concluding that the proportion of defects from scratches is…What is the adjusted p-value between the shade treatment and the dark treatment? $Treatment light-dark shade-dark shade-light O 0.7 <0.0000001 O 0.0002834 O 0.0000185 diff lwr upr p adj 0.4 0.2588299 0.5411701 0.0000185 0.7 0.5588299 0.8411701 0.0000000 0.3 0.1588299 0.4411701 0.0002834gender drug pain male 12.39867 female A 7.686667 male C 14.01467 female А 9.693333 male 11.64667 female A 8.888667 female A 6.942667 female 2.130667 female A 7.26 female A 5.868667 male В 12.93 female C 12.19333 female A 7.196667 male C 13.88 male A 8.182667 male В 16.636 female C 9.413333 male C 11.20733 female B 8.352 male A 7.243333 female A 6.806 male B 9.808667 female A 6.668667 female A 6.984667 female A 7.072 female C 2.404667 male В 7.84 female В 3.838 male 9.418 male A male A 7 female A male A 8. This exercise calls on the data set “analgesics ,". The data set contains the following variables: Gender: male or female Drug: which of three drugs was administered, A, B, or C Pain: the patient's level of pain, with a higher value representing greater pain. You first create a table showing the average level of pain for each drug/gender combination. Put "Gender" in the rows of the table and "Drug" in the Columns. After making observation on differences in the effectiveness of the…
- Specificity of the association is best described as A. when the value of the response variable changes in a meaningful way with the dosage of the suspected cause. B. when the suspected cause precedes the response variable. C. when similar studies produce similar results. D. when all other possible causes are ruled out.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. A- 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. B- Suppose we eventually plan to accumulate 50 MIcases during the period 2010–2015. Assume that the24-hour case-fatality rate is truly 20% during this period.How much power would such a study have in distinguishingbetween case-fatality rates in 2000 and 2010–2015 if atwo-sided test with significance level .05 is planned?Renal Disease Suppose ten patients with advanced diabetic nephropathy (kidney complications of diabetes) were treated with captopril over an 8-week period. Urinary protein was measured before and after drug therapy, with results listed in the table below in both the raw and In scale. (Let population 1 be the measurement after treatment and population 2 be the measurement before treatment. Use after - before.) Changes in urinary protein after treatment with captopril Patient 1 2 3 4 5 6 7 8 9 10 Raw scale urinary protein (g/24 hr) Before USE SALT 25.7 17.1 15.9 10.5 8.1 7.8 5.7 5.5 5.0 4.8 After 10.2 5.6 5.7 3.5 6.4 0.8 6.2 4.6 2.1 2.8 In scale urinary protein (g/24 hr) Before 3.2465 2.8391 2.7663 2.3514 2.0919 2.0541 1.7405 1.7047 1.6094 1.5686 After 2.3224 1.7228 1.7405 1.2528 1.8563 -0.2231 1.8245 1.5261 0.7419 1.0296 (a) What is the appropriate statistical procedure to test whether mean urinary protein has changed over the 8-week period? (You may need to use the Distribution…
- The decrease in the occurrence of new cases: Select one: a. does not affect prevalence b. increases morbidity O c. increases prevalence O d. decreases prevalenceRepeated measurement from the same individuals is an example of data collected from two related populations. True False O It cannot be determined from the information given.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.