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Q1) In 1982, CDC report explained that 3 persons who had before received whole blood transfusions developed acquired immuno deficiency syndrome (AIDS). In 1948, after discorvery of human Immuno deficiency virus (HIV), 5 companies were licensed to produce enzyme- linked immunos orbent assay(EIA, then called ELISA) test. Kits for detecting HIV antibody. In march, 1985, first kit was approved by FDA. Numerous complex issues were explained even before licensure such as false positive test results to find out whether test- positive blood donors must be notified. It is now march2, 1985. First HIV antibody test kits will arrive in blood banks in state in few hours, meeting with state Epidemiologist to explain suitable use of this test are commissioner of health , medical director of regional blood bank, and chief of state drug abuse commissioner.
To help discussion, state epidemiologist turns to pre licensure information regarding sensitivity and specificity of test kit A. Information points out that sensitivity of test kit a is 95% and specificity is 98%.
Using a separate 2 by 2 table, compute predictive value positive and predictive value negative for population of 1,000 drug users. Suppose that actual prevalence of HIV antibody among intravenous drug users is 10.0%
To determine whether there exists mean difference among the groups:
Questions based on binomial distribution, variance of the binomial distribution, discrete random variable and continuous random variables.
Suppose that an IQ test was given to a large group of persons, the scores are assumed to be from a normally distributed population, that mean = 100 and s (standard deviation) = 15.
To test whether or not there is a difference between treatments A, B, and C, a sample of 12 observations has been randomly assigned to the 3 treatments.
Testout the significance of the sample correlation also develop regression equation with scatter plot. Calculate chi-square is less than the critical value
Determine the mean number of times the machine was used per day.
Compare your best difference to the result from an ordinary two-sample t-test between these groups. Comment the difference.
Using the 0.01 significance level, can we conclude that there is a positive correlation between the variables?
Is there evidence of a difference in objection to sharing information among the organizational groupings? (use α = 0.05)
Jamie expects that a bulb will last for 400 to 500 days, what is the probability of an Acme bulb satisfying that?
Would Kruskal-Wallis be the suitable statistical procedure to test this Research Question (RQ)? Describe your answer. When would you use Chi-Square test rather than One-Way Anova?
At.05 significance level, can we conclude that larger proportion of the agents think the economy is expanding this month?
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