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M650

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Statistics

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Jan 9, 2024

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docx

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M650 Question 1 Assume the following joint and marginal probabilities: P(Male | Republican) is a ________ probability.  Joint  Conditional  Marginal Question 2 Given the following partial relative frequency table Republican Democrat Independent Male 0.188 0.191 0.169 Female 0.118 0.197 ? Compute P(Female | Democrat) and enter your answer with 3 decimal places.  0.507 Question 3 Given the following partial relative frequency table Republican Democrat Independent Male 0.158 0.146 0.116 Female 0.110 0.186 ? Compute P(Republican | Male) and enter your answer with 3 decimal places.  0.520 Question 4 Assume breast cancer affects 0.002 of the female population between 45 and 55 years of age. There are two kinds of positive test results:

M650 o True positive (the test indicates you have a disease, and you actually have it) o False positive (the test indicates you have a disease, but you actually do not have it). Assume mammograms are o 0.93 accurate detecting people who actually have breast cancer (true positive rate) o 0.94 accurate for people who do not have breast cancer (true negative rate). Compute the probability that a female who tests positive for breast cancer has breast cancer and enter your answer with 3 decimal places.  0.030 Question 5 Choose all of the correct answers for the characteristics of a Binomial Probability Distribution.  The binomial trials are dependent on each other.  The binomial trials are independent of each other.  An example of a binomial trial is rolling a die.  There can be three or more outcomes of each binomial trial.  Each binomial trial has only 2 possibilities.  An example of a binomial trial is flipping coins.  The variables are continuous.  The variables are discrete. Question 6 (7/8) Select all correct answers for the Poisson probability distribution.  The variable in a Poisson trial is counted.  The Poisson distribution describes a situation where the probability of success does not remain the same from trial to trial.  The Poisson distribution describes the number of events occurring in a unit of space or time.  The Poisson distribution's mean=median=mode.  An example of a Poisson trial is counting the number of misspelled words in a magazine article.  The variables in a Poisson trial are measured.  An example of a Poisson trial is selecting the members of a committee from one business.  The Poisson distribution is always positively skewed. Question 7

M650 Misa earned a score of 90 on her latest exam. The professor determined that all of the scores from this exam had a normal distribution with a mean of 89 and a standard deviation of 2. What is Misa's Z score on her exam? Round to three decimal digits.  0.5 Question 8 Blue Crab lengths have a normal distribution with a mean of 3 inches and a standard deviation of 2 inches. What is the Z value of 10 inches? Round to three decimal digits.  3.5 Question 9 In every normal distribution  The mean and the median are equal.  The mean is larger than the standard deviation  The mean = 0 and the standard deviation = 1  The interquartile range covers 68% of the values Question 10 The Standard Normal Distribution is a Normal Distribution with the following characteristics:  The mean is 1 and the standard deviation is 0  The mean is 0 and the standard deviation is 1  The mean and the standard deviation are 0  The mean and the standard deviation are 1 Question 11 In a normal distribution, the probability of a value larger than 1 standard deviation above the mean is:  32%  16%

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M650  68%  There is not enough information to answer the question Question 12 In a normal distribution the probability of a value between 2 and 3 standard deviations below the mean is:  .15%  2.35%  -.15%  -2.35%

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