The formula for the family-wise error rate when conducting multiple comparisons with t-tests is 1 - (1 - α)c. Could you intuitively explain where this formula comes from? That is, why does subtracting the quantity (1 - α)c from one calculate the cumulative probability of a type I error?
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The formula for the family-wise error rate when conducting multiple comparisons with t-tests is 1 - (1 - α)c.
Could you intuitively explain where this formula comes from? That is, why does subtracting the quantity (1 - α)c from one calculate the cumulative
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- 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. 7.14 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.you are conducting a study to see if the average female life expectancy is significantly different from 99. Your sample data (n=13) produce the test statistic t=-2.87. Find the p-value accurate to 4 decimal places. You are conducting a study to see if the probability of catching the flu this year is significantly more than 0.28. Your sample data produce the test statistic z=1.64. Find the p-value accurate to 4 decimal places. You are conducting a study to see if the accuracy rate for fingerprint identification is significantly less than 0.1. Your sample data produce the test statistic z=-1.747 . Find the p-value accurate to 4 decimal places.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.
- You are a researcher who wants to know what the mean (µ) level of anxiety would be for the whole population if they were all receiving a new anti-anxiety therapy. You can’t give the therapy to the whole population, so you give it to a sample, and you get M = 32.1 as the average anxiety level for the sample on the therapy. What is the reason that you can’t just simply assume that µ = 32.1? You didn’t use random assignment Sampling error Descriptive statistics Inferential statisticsYou are conducting a study to see if the probability of catching the flu this year is significantly different from 0.75. Your sample data produce the test statistic z=−1.933z=-1.933. Find the p-value accurate to 4 decimal places.Sixty teachers were interviewed regarding their opinion on the issue of increasing the number of years of basic education from 10 to 12years. Do these teachers differ significantly in their opinion on this issue? Test the claim at α=0.05. Agree – 32, Disagree – 10, Undecided – 18 What is the tabulated value and the statistical value?
- 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?A researcher conducted a Chi-square test to determine whether the progeny of oyster mushroom follows the ratio of 3 grey: 1 white. From his calculation, he found his calculated Chi-square is smaller than the critical Chi-square value from the table. Which one is the CORRECT conclusion? a. Null hypothesis cannot be rejected. The progeny ratio is different than the expected ratio. b. Null hypothesis is rejected. The progeny ratio follows the expected ratio. c. The ratio of the progeny from his experiment does not follow the ratio 3:1. d. The ratio of the progeny from his experiment is consistent with the ratio 3:1.How would you figure this out? I had gotten the first two wrong.
- Suppose data shows that only 50% of breast cancer patients can survive more than 5 years. You suspect the percentage is too low, so you'd like to conduct a study to examine this situation. What is the null and alternative hypothesis in this situation?Suppose X-N(10,sigma=2), what is the z-score of x = 7.
