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No If the TRUE variance of the sampling distribution was known, then it would be appropriate to use a t, distribution to construct confidence intervals for the mean. Yes A "statistically significant" result is one that is unlikely under assump- True False tions we made about the theoretical world. Suppose that we are interested in testing the following hypotheses about a proportion: Họ : p = 0.4 versus Ha : p < 0.4. Some data are collected and the value of the test statistic is 1.2. Should the conclusion at Yes No a = 0.05 be to reject Ho?

No If the TRUE variance of the sampling distribution was known, then it would be appropriate to use a t, distribution to construct confidence intervals for the mean. Yes A "statistically significant" result is one that is unlikely under assump- True False tions we made about the theoretical world. Suppose that we are interested in testing the following hypotheses about a proportion: Họ : p = 0.4 versus Ha : p < 0.4. Some data are collected and the value of the test statistic is 1.2. Should the conclusion at Yes No a = 0.05 be to reject Ho?

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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If the TRUE variance of the sampling distribution was known, then it would be appropriate to use a t- distribution to construct confidence intervals for the mean. 1 Yes No A "statistically significant" result is one that is unlikely under assump- True False tions we made about the theoretical world. Suppose that we are interested in testing the following hypotheses about a proportion: Ho : p = 0.4 versus H. : p< 0.4. Some data are collected and the value of the test statistic is 1.2. Should the conclusion at Yes No a = 0.05 be to reject Ho? To construct an 80% confidence interval for a population proportion using a random sample of size meeting the Success- Failure condition, you use the normal distribution table. Write the Z-value Anecdotal evidence is useful for statistical inference. Replication in the context of design of an experiment is ensuring the True False study can be repeated by other investigators. Blinding is the practice of making the assigned treatment unknown to experimental units and/or the person administering the treatment. Two events A and B are independent if P(A|B) = P(B). The t confidence interval for the true mean is robust to minor deviations 4 True False 7 True False 8 True False 9. True False from the Normal distribution. 10 Even if the null hypothesis were true, if you carry out a test repeatedly True with independent random samples of the same size, you will reject the null hypothesis a x 100% (where a is the significance level) of the time. 11 For the linear regression y = bo+ bịlog10(x), if x is divided by 10, then y increases by b1. 12 If X is a random variable, then Var(X) is also a random variable. 13 For proportions measured in two related groups, the formula for the True | False 95% confidence interval for p1 – P2 is ĝi – P2 ±1.96/ False True False True False P1 (1-p1) P2(1-p2) n2 14 The statement "The regression line passes through the point (7, j) " is True False always true. 15 On 31 observational units you obtained measurements on a pair of variables X and Y. You fitted a linear regression model. To test a hypothesis on the slope (B1) of Y on X, you use a t-statistic which follows a t-distribution under Ho : B1 = 0. What is the degrees of freedom of this t-distribution? 16 Suppose we flipped a beer cap 10, 000 times and observed that the red True side of the cap came up 5141 times. We can use a binomial model with n = 10,000 and p = 0.5141 to draw statistical inference as this is the true model for the flipping a beer cap experiment. False
Transcribed Image Text:If the TRUE variance of the sampling distribution was known, then it would be appropriate to use a t- distribution to construct confidence intervals for the mean. 1 Yes No A "statistically significant" result is one that is unlikely under assump- True False tions we made about the theoretical world. Suppose that we are interested in testing the following hypotheses about a proportion: Ho : p = 0.4 versus H. : p< 0.4. Some data are collected and the value of the test statistic is 1.2. Should the conclusion at Yes No a = 0.05 be to reject Ho? To construct an 80% confidence interval for a population proportion using a random sample of size meeting the Success- Failure condition, you use the normal distribution table. Write the Z-value Anecdotal evidence is useful for statistical inference. Replication in the context of design of an experiment is ensuring the True False study can be repeated by other investigators. Blinding is the practice of making the assigned treatment unknown to experimental units and/or the person administering the treatment. Two events A and B are independent if P(A|B) = P(B). The t confidence interval for the true mean is robust to minor deviations 4 True False 7 True False 8 True False 9. True False from the Normal distribution. 10 Even if the null hypothesis were true, if you carry out a test repeatedly True with independent random samples of the same size, you will reject the null hypothesis a x 100% (where a is the significance level) of the time. 11 For the linear regression y = bo+ bịlog10(x), if x is divided by 10, then y increases by b1. 12 If X is a random variable, then Var(X) is also a random variable. 13 For proportions measured in two related groups, the formula for the True | False 95% confidence interval for p1 – P2 is ĝi – P2 ±1.96/ False True False True False P1 (1-p1) P2(1-p2) n2 14 The statement "The regression line passes through the point (7, j) " is True False always true. 15 On 31 observational units you obtained measurements on a pair of variables X and Y. You fitted a linear regression model. To test a hypothesis on the slope (B1) of Y on X, you use a t-statistic which follows a t-distribution under Ho : B1 = 0. What is the degrees of freedom of this t-distribution? 16 Suppose we flipped a beer cap 10, 000 times and observed that the red True side of the cap came up 5141 times. We can use a binomial model with n = 10,000 and p = 0.5141 to draw statistical inference as this is the true model for the flipping a beer cap experiment. False
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