| | | | Practice Test 2 BUSI 3311 |
| Question 1: The time to download a new YouTube video is normally distributed with a mean |
| | of 12 seconds and standard deviation of 3 seconds |
| a. What is the probability that the time to download the video will be less than 9 seconds |
| | during the next download? |
| | | https://getmeaplus.com/ |
| b. What is the probability that the time to dowload will be between 9 and 11 seconds during |
| | the next download? |
| c. What is the probability that the time to download will be greater than 13 on |
| | the next download? |
| d. YouTube is concerned with downloads that take "too long." They define "too long" as |
| | the top 5%. At approximately what time should YouTube be notified? |
| Question 2: If the average number of cars sales per month is 150, the population standard |
| | deviation is known to be 25, and the sample size is 20. |
| a. Construct a 95% confidence interval for the population mean |
| | | | | | | lower limit | upper limit |
| Question 3: Assuming the population is normally distributed, construct a 95% confidence |
| | interval for the population mean, based on the following sample |
| Sample | 4, 6, 6, 7, 8, 9, 9, 12, 15 |
| Average |
| Standard deviation |
| Sample size |
| Degrees of Freedom |
| tα/2 |
| Confidence Interval | | 95% | Interval lower limit |
| | | 95% | Interval upper limit |
| Question 4: A company produces light bulbs and advertises that their light bulbs last |
| | 2,000 hours. Use the data below to conduct a 95% confidence on the light bulb hrs. |
| Sample of light bulbs shows the following bulb life |
| | 1702, 1832, 1909, 1955, 1987, 2012, 2332, 2422, 2439, 2453, 2566, 2643, 2677, 2701 |
| Average |
| Standard deviation |
| Sample size |
| Degrees of Freedom |
| tα/2 |
| 95% | Interval lower critical level |
| 95% | Interval upper critical level |
| Based on your results, can you safely state that the company advertising is fair? |
| Question 5: The marketing manager has stated that she believes that weekly product sales |
| | are limited at some of the stores based on the amount of shelf space provided. |
| She takes a random sample of 12 stores to determine if shelf space is related |
| | to weekly sales. She gets the following results from her linear regression |
| | y= 7.4x + 145 | | y is shelf space |
| | R2 = .6839 | | x is sales |
| a. How much variance in weekly sales does shelf space explain? |
| b. What is the coefficient of correlation (r)? |
| c. How would you rate this relationship (strong positive, weak negative, etc.) |
| d. Should you feel comfortable using this to predict sales using shelf space? |
| e. How much would you expect sales to be at a store with 12 feet of shelf space? |
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practice_test_2_summer2017.xlsx
