1.2.1* After you conduct a coin-flipping simulation, a graph of the 0.5. Choose
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1.2.1* After you conduct a coin-flipping simulation, a graph of the 0.5. Choose from (A) (D). will be centered very close to A. Proccss B. Sample size C. Number of heads D. Proportion of heads 1.2.2 The graph of a Class null distribution will be centered approximately on: A. The observed proportion B. The observed count C. The value of the probability in the null hypothesis D. The number of repetitions performed 1.2.3* The p-value of test of significance is: A. The probability, assuming the null hypothesis is true, that we would get a result as extreme as the one that was actually observed. B. The probability, assuming the alternative hypothesis is truc, that we would get a result as extreme as the one that was actually obscrved. C. The probability the null hypothesis is truc. D. The probability the alternative hypothesis is true. 1.2.4 Suppose a researcher is testing to see if a basketball player can make free throws at a rate higher than the NBA average of 75%. The player is tested by shooting 10 free throws and makes 8 of them. In conducting the related test of significance, we have a computer applet do an appropriate simulation, 1000 repetitions, and produce a null distribution. This distribution represents: A. Repeated results if the player makes 80% of his shots in the long run. B. Repeated results if the player makes 75% of his shots in the long run. C. Repeated results if the player makes more than 75% of his shots in the long run. D. Repeated results if the player makes more than 80% of his shots in the long run.Explanation / Answer
1,2.1 - Ans is (C) (Number of Heads). In coin flipping simulation, as the number of flips go on increasing, the proportion of Heads and Tails should APPROACH the value of 0.5. Here approach is emphasized, because it is not implied that the proportion is exactly 0.5. However it should be very close to that value. That is because the Heads and Tails are unbiased events. So the empirical probability from experiment should be very close to the theoretical probability
1.2.2 - Ans is (C) (Value of probability in Null Hypothesis). A null hypothesis is one for which the null hypothesis is true. The condition for that is, the distribution should be centred around the hypothesized probability value
1.2.3 - Ans is (A). This is the very definition of the p-value, viz. the test statistic. Generally, a p-value of 0.05 or 0.01 is used, which means that we want to have a 95% or 99% level of confidence on our observations. The p-value helps us decide whether to accept or reject the null hypothesis.
1.2.4 - Ans is (C). We are interested in comparing the player's success rate against the NBA average of 75%, and there is no other comparison that we are interested in. So we shall like to see if his shot making rate is more than 75%.
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