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What is a representative sample? What is its value?

Short Answer

Expert verified

The representative sample is the group that provides information on the entire population and is of great value for researchers and statisticians.

Step by step solution

01

Definition of a representative sample

A representative sample can be understood as the subset of the population that accurately indicates the attributes of the population considered for the study.

Example: Consider an organization with 500 employees bifurcated into 250 male employees and 250 female employees. Then the sample of 100 employees with 50 male and 50 female is an example of a representative sample.

02

Value of representative sample

The representative sample is important in statistics as it facilitatesacquiring information about the population just by studying the sample, which is a smaller group. For statisticians and researchers, studying details about the entire population is time-consuming; moreover, money and resources are spent on it; hence, studying the sample that comprises the characteristics of the entire population makes it easy and more convenient for them. Accordingly, the statistician can conclude and provide the required results in a shorter period along with utilizing lower resources.

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Most popular questions from this chapter

Guilt in decision making. The effect of guilt emotion on how a decision maker focuses on the problem was investigated in the Journal of Behavioral Decision Making (January 2007). A total of 171 volunteer students participated in the experiment, where each was randomly assigned to one of three emotional states (guilt, anger, or neutral) through a reading/writing task. Immediately after the task, the students were presented with a decision problem (e.g., whether or not to spend money on repairing a very old car). The researchers found that a higher proportion of students in the guilty-state group chose to repair the car than those in the neutral-state and anger-state groups.

a. Identify the population, sample, and variables measured for this study.

b. Identify the data-collection method used.

c. What inference was made by the researcher?

d. In later chapters you will learn that the reliability of an inference is related to the size of the sample used. In addition to sample size, what factors might affect the reliability of the inference drawn in this study?

Explain how populations and samples differ?

Can money spent on gifts buy love? Is the gift you purchased for that special someone really appreciated? This was the question of interest to business professors at Stanford University. Their research was published in the Journal of Experimental Social Psychology (Vol. 45, 2009). In one study, the researchers investigated the link between engagement ring price (dollars) and level of appreciation of the recipient (measured on a 7-point scale where 1 = โ€œnot at allโ€ and 7 = โ€œto a great extentโ€). Participants for the study were those who used a popular Web site for engaged couples. The Web siteโ€™s directory was searched for those with โ€œaverageโ€ American names (e.g., โ€œJohn Smith,โ€ โ€œSara Jonesโ€). These individuals were then invited to participate in an online survey in exchange for a $10 gift certificate. Of the respondents, those who paid really high or really low prices for the ring were excluded, leaving a sample size of 33 respondents.

a. Identify the experimental units for this study.

b. What are the variables of interest? Are they quantitative or qualitative in nature?

c. Describe the population of interest.

d. Do you believe the sample of 33 respondents is representative of the population? Explain.

e. In a second designed study, the researchers investigated whether the link between gift price and level of appreciation is stronger for birthday gift-givers than for birthday gift-receivers. The participants were randomly assigned to play the role of gift-giver or gift-receiver. Assume that the sample consists of 50 individuals. Use a random number generator to randomly assign 25 individuals to play the gift-receiver role and 25 to play the gift-giver role.

The โ€œlucky store effectโ€ in lottery ticket sales. In the American Economic Review (Vol. 98, 2008), University of Chicago researchers investigated the lucky store effect theory in lottery ticket sales, i.e., the theory that a lottery retail store that sold a large-prize-winning ticket will experience greater ticket sales the following week. The researchers examined the weekly ticket sales of all 24,400 active lottery retailers in Texas. The analysis showed that โ€œthe week following the sale of [a winning Lotto Texas ticket], the winning store experiences a 12 to 38 percent relative sales increase. . . . โ€ Consequently, the researchers project that future winning lottery retail stores will experience the lucky store effect. Is this study an example of descriptive statistics or inferential statistics? Explain.

Structurally deficient highway bridges. Refer to Exercise 1.29. The NBI data were analyzed and the results made available at the FHWA Web site (www.fhwa.dot.gov). Using the FHWA inspection ratings, each of the 608,272 highway bridges in the United States was categorized as structurally deficient, functionally obsolete, or safe. About 13.5% of the bridges were found to be structurally deficient, while 3.5% were functionally obsolete.

a. What is the variable of interest to the researchers?

b. Is the variable of part a quantitative or qualitative?

c. Is the data set analyzed a population or a sample? Explain.

d. How did the NBI obtain the data for the study?

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