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A statistics exam focused on sampling distributions and estimation techniques. It includes problems related to approximating sampling distributions with normal probability distributions, determining appropriate sample sizes for estimating population parameters, and calculating probabilities related to sample means. Each problem is accompanied by a detailed answer key, providing step-by-step solutions and explanations. The exam covers key concepts such as the central limit theorem, standard deviation, and z-scores, offering valuable practice for students studying introductory statistics. It also includes instructor comments on one of the answers.
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MATH 110 - Introduction to Statistics Module 5 Exam Exam Page 1 Suppose that you take a sample of size 50 from a population that is not normally distributed. Can the sampling distribution of x̄ be approximated by a normal probability distribution? Yes, the sample size can be approximated by a normal probablity ditribution because the sample size is greater than 30.
n ≤ (0.05 x 1200 ) = 60 n ≤ 60 The sample size (n) has to be less than or equal to 60 n ≤ 60 The sample size (n) has to be less than or equal to 60
Exam Page 4 Suppose that in a very large city 9.8 % of the people have more than two jobs. Suppose that you take a random sample of 70 people in that city, what is the probability that 9 % or more of the 70 have more than two jobs? We want P(Z>-0.23). From the standard normal table, we find: P(Z>-.23)=1- P(Z<-.23)=1-.40905=.59095. So there is a .60257 probability that the percentage of the sample that have more than two jobs is more than 9 %. -1.0 points Instructor Comments The value stated in the conclusion is not correct.