Please answer the following questions for the three examples on Chapter 1 Sectio
ID: 3353769 • Letter: P
Question
Please answer the following questions for the three examples on Chapter 1 Section 1.4
Example 1.1 The cell phone case: Reducing cellular phone costs
1)Please define the element for the example? What are the variables?
2)Based on the table(s) or figure(S) from the example, please determine whether the data set is quantitative data or qualitative (i.e. categorical) data. Please further define if it is ratio, interval, ordinal, or nominative variable.
3)Based on the table(s) or figure(S) from the example, please determine whether the data set is cross-sectional data or time-series data.
4)Based on the example, please determine where the data comes from (i.e. “existing sources” or “experimental and observational studies”).
5)Based on the example, please determine if the example is a census study. If not, what are the population and sample size for the example?
6)Based on the example, is it the case of descriptive statistics or a study of statistical inference?
Example 1.2 The marketing research case: Rating a bottle design
1)Please define the element for the example? What are the variables?
2)Based on the table(s) or figure(S) from the example, please determine whether the data set is quantitative data or qualitative (i.e. categorical) data. Please further define if it is ratio, interval, ordinal, or nominative variable.
3)Based on the table(s) or figure(S) from the example, please determine whether the data set is cross-sectional data or time-series data.
4)Based on the example, please determine where the data comes from (i.e. “existing sources” or “experimental and observational studies”).
5)Based on the example, please determine if the example is a census study. If not, what are the population and sample size for the example?
6)Based on the example, is it the case of descriptive statistics or a study of statistical inference?
Example 1.3 The car mileage case: Estimating mileage
1)Please define the element for the example? What are the variables?
2)Based on the table(s) or figure(S) from the example, please determine whether the data set is quantitative data or qualitative (i.e. categorical) data. Please further define if it is ratio, interval, ordinal, or nominative variable.
3)Based on the table(s) or figure(S) from the example, please determine whether the data set is cross-sectional data or time-series data.
4)Based on the example, please determine where the data comes from (i.e. “existing sources” or “experimental and observational studies”).
5)Based on the example, please determine if the example is a census study. If not, what are the population and sample size for the example?
6)Based on the example, is it the case of descriptive statistics or a study of statistical inference?
C EXAMPLE 1.2 The Cell Phone Case: Reducing Cellular Phone Costs Part 1: The Cost of Company Cell Phone Use Rising cell phone costs have forced companies having large numbers of cellular users to hire services to manage their cellular and other wireless resources. These cellular management services use sophisticated software and mathematical models to choose cost-efficient cell phone plans for their clients. One such firm, mind Wireless of Austin, Texas, specializes in automated wireless cost management. According to Kevin Whitehurst, co-founder of mindWireless, cell phone carriers count on overage-using more minutes than one's plan allows—and underage—using fewer minutes than those already paid for—to deliver almost half of their revenues. As a result, a company's typical cost of cell phone use can be excessive-18 cents per minute or more. However, Mr. Whitehurst explains that by using mindWireless automated cost management to select calling plans, this cost can be reduced to 12 cents per minute or less. In this case we consider a bank that wishes to decide whether to hire a cellular management service to choosc its employees' calling plans. While the bank has over 10,000 employees on many different types of calling plans, a cellular management service suggests that by studying the calling patterns of cellular users on 500-minute-per-month plans, the bank can accurately assess whether its cell phone costs can be substantially reduced. The bank has 2,136 employees on a variety of 500-minute-per-month plans with different basic monthly rates, different overage charges, and different additional charges for long distance and roaming. It would be extremely time-consuming to analyze in detail the cell phone bills of all 2,136 employees. Therefore, the bank will estimate its cellular costs for the 500-minute plans by analyzing last month's cell phone bills for a random sample of 100 employees on these plans. Part 2: Selecting a Random Sample The first step in selecting a random sample is to obtain a numbered list of the population elements. This list is called a frame. Then we can use a random number table or computer-generated random numbers to make random selections from the numbered list. Therefore, in order to select a random sample of 100 employees from the population of 2,136 employees on 500-minute-per-month cell phone plans, the bank will make a numbered list of the 2,136 employees on 500-minute plans. The bank can then use a random number table, such as Table 1.4(a) on the next page, to select the random sample. To see how this is done, note that any single-digit number in the table has been chosen in such a way that any of the single-digit numbers between 0 and 9 had the same chance of being chosen. For this reason, we say that any single-digit number in the table is a random number between 0 and 9. Similarly, any two-digit number in the table is a random number between 00 and 99, any three-digit number in the table is a random number between 000 and 999, and so forth. Note that the table entries are segmented into groups of five to make the table easier to read. Because the total number of employees on 500-minute cell phone plans (2,136) is a four-digit number, we arbitrarily select any set of four digits in the table (we have circled these digits). This number, which is 0511, identifies the first randomly selected employee. Then, moving in any direction from the 0511 (up, down, right, or left-it does not matter which), we select additional sets of four digits. These succeeding sets of digits identify additional randomly selected employees. Here we arbitrarily move down from 0511 in the table. The first seven sets of four digits we obtain are 0511 7156 0285 4461 3990 4919 1915 (See Table 1,4—these numbers are enclosed in a rectangle.) Because there are no employees numbered 7156, 4461, 3990, or 4919 (remember only 2,136 employees are on 500-minute plans), we ignore these numbers. This implies that the first three randomly selected employees are those numbered 0511,0285, and 1915. Continuing this procedure, we can obtain the entire randon sample of 100 employees. Notice that, because we are sampling without replacement, we should ignore any set of four digits previously selected from the random number table. While using a random number table is one way to select a random sample, this approach has a disadvantage that is illustrated by the current situation. Specifically, because most four-digit random numbers are not between 0001 and 2136, obtaining 100 different, four-digit random numbers between 0001 and 2136 will require ignoring a large number of random numbers in the random number table, and we will in fact need to use a random number table that is larger than Table 1.4. Although larger random number tables are readily available in books of mathematical and statistical tables, a good alternative is to use a computer 12 TABLE 1.4 Random Numbers (a) A portion of a random number table 3327685590 79936 5686505859 90106 78188 03427 9651 69445 18663 7269552180 90322 (b) Minitab output of 100 different, four-digit random numbers between 1 and 2136 705 1131 169 1703 1709 609Explanation / Answer
EXAMPLE 1.2
1) Element of the example is bottle design. Variables of this bottle is design, shape. readable label, bottle cap and bottle apearance.
2) THE QUESTION DATA SET IS CATEGORICAL (ORDINAL VARIABLE) AND THE OVERALL SCORE DATA SET IS QUANTITATIVE RATIO VARIABLE
3) CROSS SECTIONAL DATA
4) The data comes from existing sources.
5) NO EXAMPLE IS NOT CENSUS STUDY. POPULATION IS MALL POPLATION. AND SAMPLE IS SHOPPERS OF THAT MALL AT PARTICULAR SATURDAY.
6) BASED ON THE EXAMPLE IT IS DESCRIPTIVE STATISTICS STUDY.
PLEASE NOTE: I HAVE DONE EXAMPLE 1.3 . PLEASE REPOST OTHERS . THANK YOU.