Qnt 561 Week 3 Assessment Questions

Exercises 21, 22, and 34 (Ch. 8) of Statistical Techniques in Business & Economics

21. What is sampling error? Could the value of the sampling error be zero? If it were zero, what would this mean?

Sampling error is defined by Lind, Marchal & Wathen as the difference between a sample statistic and its corresponding population parameter (2008). Example: a sample showed that 10% of hotel guest prefer fried eggs over scrambled eggs. Since this is a sample, we can’t say for sure that ALL guest prefer fried eggs; there will be a difference (sample error) between the sample and the results if questioned every guest.

22. List the reasons for sampling. Give an example of each reason for sampling.

Reasons for sampling, “To contact the whole population would be time consuming, the cost of studying all the items in a population may be prohibitive, the physical impossibility of checking all items in the population, the destructive nature of some tests and the sample results are adequate” (Lind, Marchal & Wathen, p. 261-62, 2008).

Examples of each reason for sampling:

Time consuming – If a large retail store wanted to survey every customer to determine the desire for a new product, they would want to send a survey to a sample set of customers because sending a survey to each customer would be very time consuming.

Cost Prohibitive – Another reason for sampling is costs. In the above example, it would been simply too expensive to survey every single customer. The cost for sampling is much lower.

Physical Impossibility – If the large retail store had 1 million customers and sampled all the customers it would take a very long time and a great deal of manpower to tally the results.

Destructive nature of some test – A restaurant chief must sample the food the restaurant is preparing, however he can’t taste an item from each plate. Therefore, he tastes a sample set of food each night.

Sample results are adequate – I worked for an insurance...