12 Chapter 1 Basic Ideas 42. The tax man cometh: The Internal Revenue Service wants to sample 1000 tax returns that were submitted last year to determine the percentage of returns that had a refund. Describe a sampling method that would be appropriate in this situation. Explain your reasoning. Extending the Concepts 43. Draw a sample: Imagine that you are asked to determine students’ opinions at your school about a potential change in library hours. Describe how you could go about getting a sample of each of the following types: simple random sample, sample of convenience, voluntary response sample, stratified sample, cluster sample, systematic sample. 44. A systematic sample is a cluster sample: Explain how a systematic sample is actually a type of cluster sample. Answers to Check Your Understanding Exercises for Section 1.1 1. No; this sample consists only of people in the town who visit the mall. 2. Yes; every group of n customers, where n is the sample size, is equally likely to be chosen. 3. Voluntary response sample 4. Cluster sample 5. Stratified sample 6. Systematic sample SECTION 1.2 Types of Data Objectives 1. Understand the structure of a typical data set 2. Distinguish between qualitative and quantitative variables 3. Distinguish between ordinal and nominal variables 4. Distinguish between discrete and continuous variables Objective 1 Understand the structure of a typical data set Data Sets In Section 1.1, we described various methods of collecting information by sampling. Once the information has been collected, the collection is called a data set. A simple example of a data set is presented in Table 1.1, which shows the major, final exam score, and grade for several students in a certain statistics class. Table 1.1 Major, Final Exam Score, and Grade for Several Students Student Major Exam Score Grade 1 Psychology 92 A 2 Business 75 B 3 Communications 82 B 4 Psychology 72 C 5 Art 85 B Table 1.1 illustrates some basic features that are found in most data sets. Information is collected on individuals. In this example, the individuals are students. In many cases, individuals are people; in other cases, they can be animals, plants, or things. The characteristics of the individuals about which we collect information are called variables. In this example, the variables are major, exam score, and grade. Finally, the values of the variables that we obtain are the data. So, for example, the data for individual #1 are Major = Psychology, Exam score = 92, and Grade = A.
navidi_monk_essential_statistics_1e_ch1_3
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