e you do a hypothesis testing comparing two population proportions. The calculated P-value is 0.026. Which of the following is a proper conclusion? a. None of the above are proper conclusions. b. The probability that the null hypothesis is true is 0.026. c. The probability that the alternative hypothesis is true is 0.026. d. The difference in population proportions is 0.026. e. The difference
Contingency Table
A contingency table can be defined as the visual representation of the relationship between two or more categorical variables that can be evaluated and registered. It is a categorical version of the scatterplot, which is used to investigate the linear relationship between two variables. A contingency table is indeed a type of frequency distribution table that displays two variables at the same time.
Binomial Distribution
Binomial is an algebraic expression of the sum or the difference of two terms. Before knowing about binomial distribution, we must know about the binomial theorem.
1. Suppose you do a hypothesis testing comparing two population proportions. The calculated P-value is 0.026. Which of the following is a proper conclusion?
a. None of the above are proper conclusions.
b. The
c. The probability that the alternative hypothesis is true is 0.026.
d. The difference in population proportions is 0.026.
e. The difference in sample proportions is 0.026.
2. How much more effective is exercise plus drug treatment in reducing the rate of heart attack among women aged 60 and above compared to drug treatment alone? A research was conducted to check whether drug treatment plus exercise is better in reducing heart attacks compared to drug treatment alone. A completely randomized experiment was done to 1000 healthy females aged 60 and above. Five hundred of subjects received drug treatment only, while the remaining five hundred must do exercise while receiving the treatment. What must be the most appropriate inference method for the original research question?
a. one-sample z test for a proportion
b. two-sample t test for μ1 - μ2
c. two-sample z interval for p1 - p2
d. two-sample t interval for μ1 - μ2
e. two-sample z test for p1 - p2
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