The shape of the binomial distribution is always symmetric.

Binomial distribution is always a symmetrical distribution. True False True False. If events A and B are independent, then P(


(A) False. Binomial distribution is symmetric only for p = 0.5. i.e. probability of success is 0.5. (B) False. P(A or B) = P(A) + P(B) if A and B are mutually exclusive (C) False. The sampling distribution of sample mean bar{x} text{ is } Nleft(mu, frac{sigma^2}{n}right). text{Here we know } sigma^2 text{ but } mu text{ is unkown.} text{so } bar{x} sim Nleft(mu, 1). text{ where } mu text{ is unkown.} (D) False. text{If X and Y are independent, } sigma^2_{X+Y} = sigma^2_{X} + sigma^2_{Y}. (E) True. Population standard deviation and width (margin of error) of the confidence interval are directly proportional. (F) False. Such a study is called experimental studies or interventional studies. (E) False. The central limit theorem is applicable for large sample size only but population distribution need not be bell-shaped. (F) True. 99% C.I. will cover the value 1 as long as the p-value associated with the hypothesis is greater than 0.005. (G) True. Many test statistics takes this form. (H) False. If the test is significant at 5% level of significance, it means that if the null hypothesis was really true, there was very little chance (less than 5%) of observing the sample we have at hand.

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