Suppose the coin 0 has 0.5 chance for head, and the coin 1 has 0.7 chance for head. We toss the coins untial a head comes up, and record the total number of tosses, X. The null hypothesis(H0) is that we tossed coin0. The alternative hypothesis(H1) is that we tossed coin1. a. If the prior probabilities are equal, which outcomes favor H0? b. Suppose P(H0)/P(H1) = 10. What outcomes favor H0? c. What is the significance level of a test that rejects H0 if X is equal or greater than 8?
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.
Suppose the coin 0 has 0.5 chance for head, and the coin 1 has 0.7 chance for head. We toss the coins untial a head comes up, and record the total number of tosses, X. The null hypothesis(H0) is that we tossed coin0. The alternative hypothesis(H1) is that we tossed coin1.
a. If the prior
b. Suppose P(H0)/P(H1) = 10. What outcomes favor H0?
c. What is the significance level of a test that rejects H0 if X is equal or greater than 8?
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