302-Sp20-Assignment-1-due-March 1 (2)

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Texas A&M University, Commerce *

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302

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Economics

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May 13, 2024

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docx

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1 Eco 302: Assignment 1-Spring-2020:- Chapters: 1, 2, 3, 5, 6 & 7: Total 250 points Due by Midnight (11:59 pm), Sunday, March 1 st , 2020 True/False Questions carry 2 points each, Multiple Choices carry 4 points each and the Essay type questions carry 10 points each: total 250 points. True / False Questions (Type T for true and F for False) Chapter 1 1. An example of a quantitative variable is the telephone number of a person.  False 2. An example of a qualitative variable is the mileage of a car. False 3. Credit score is an example of an interval scale variable. True Chapter 2 4. When establishing the classes for a frequency table it is not always true that the more classes you use the better your frequency table will be. True 5.  The cumulative distribution function is initially increasing and then decreasing towards the end. False 6. The relative frequency is the frequency of a class divided by the total number of classes.  False Chapter 3 7. The income distribution is skewed to the right; therefore, the Mean Income must be greater than the Median Income. True 8. The sample standard deviation formula does not make it an unbiased estimator. True 9. The Median is the measure of central tendency that divides a population or sample into two equal parts. True Chapter 5   10. The probability of an event is a value which must be greater than 0 and less than 1. False 11. If events A and B are mutually exclusive, then P(A|B) is always equal to zero. True 12. Mutually exclusive events cannot be independent. True 13. A classical probability measure is a probability assessment that is based on relative frequency. False 14. The probability of an event is the product of the probabilities of the sample space outcomes that correspond to the event.  False
2 15. If events A and B are independent, then P(A|B) is always equal to P(A). True 16. Events that have no sample space outcomes in common and, therefore cannot occur simultaneously are referred to as mutually independent events. False   Chapter 6 17. The binomial experiment consists of n independent, identical trials, each of which results in either success or failure and the probability of success changes from trial to trial. False 18. The standard deviation of a binomial distribution is np(1-p ). False 19. In a binomial distribution the random variable X is discrete. True   Chapter 7 20. The standard deviation and mean are the same for the standard normal distribution. False 21. In a statistical study, the random variable X = 1, if the house is colonial and X = 0 if the house is not colonial, then it can be stated that the random variable is continuous. False 22.  For a continuous distribution, P(X ≤ 10) is the same as P(X<10). True 23. For a continuous distribution, the exact probability of any particular value is always zero.  True   24. For a binomial probability experiment, with n = 60 and p =.2, it is appropriate to use the normal approximation to the binomial distribution without continuity correction. False 25. All continuous random variables are normally distributed.  False Multiple Choice Questions (Answer marked with underline and bold face) Chapters 1 and 2 1. The two types of qualitative variables are:  A. Ordinal and ratio B. Interval and ordinal C.   Nominative and ordinal D. Interval and ratio E. Nominative and interval 2. Which of the following is a Nominal variable? A.  Bank Account Balance B.  Air Temperature C.  Daily Sales in a Store D.  Value of Company Stock E.   Whether a Person Has a Traffic Violation
3 3. College entrance exam scores, such as GMAT scores, are an example of a(n) ________________ variable. A. Ordinal B. Ratio C. Nominative D.   Interval 4. Which of the following is a quantitative variable?  A. The make of a TV B. The VIN of a car C.   The price of a TV D. Whether a person is a college graduate E. The Driver’s License Number 5. When developing a frequency distribution, the class (group) intervals should be  A. Large B. Small C. Mutually exclusive D. Integer E. Equal 6. If there are 125 values in a data set, how many classes should be created for a frequency histogram?  A. 4 B. 5 C. 6 D. 7 E.   8 7. An identification of police officers by rank would represent a(n) ____________ level of measurement.  A. Nominative B.   Ordinal C. Interval D. Ratio Chapter 3 8. Quality control is an important issue at ACME Company which manufacturers light bulbs. In order to conduct testing of the life hours of their light bulbs, they randomly sampled nine light bulbs and measured how many hours they lasted: 378, 361, 350, 375, 200, 391, 375, 368, and 321. What is the Variance?  A. 342.43 B.   3424.3 C. 58.5 D. 191 E. 10609
4 9. When using the Chebyshev's theorem to obtain the bounds for a 99.73 percent of the values in a population, the interval generally will be ___________ the interval obtained for the same percentage if normal distribution is assumed (empirical rule).  A.   wider than B. narrower than C. the same as 10.  According to a survey of the top 10 employers in a major city in the Midwest, a worker spends an average of 413 minutes a day on the job. Suppose the standard deviation is 26.8 minutes and the time spent is approximately a normal distribution. What are the times that approximately 95.45% of all workers will fall?  A. [387.5 438.5] B. [386.2 439.8] C. [372.8 453.2] D.   [359.4 466.6] E. [332.6 493.4] 11. The company financial officer was interested in the average cost of PCs that had been purchased in the past six months. A random sample of the price of 10 computers was taken with the following results: $3,250, $1,127, $2,995, $3,250, $3,445, $3,449, $1,482, $6,120, $3,009, $4,000 What is the median?  A. 3447 B. 3213 C. 3445 D. 6120 E.   3250 12 Find the z-score for a IQ test score of 90 when the mean is 100 and the standard deviation is 15.  A.   -0.67 B. 0.77 C. -0.77 D. 0.67 E. -10.00 Chapter 5 13. Two mutually exclusive events having positive probabilities are ______________ dependent.  A. Sometimes B.   Always C. Never 14. If events A and B are independent, then the probability of simultaneous occurrence of event A and event B can be found with:  A.  P(A)·P(B)
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