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Part 4 Sampling and Data Collection DETERMINATION OF SAMPLE SIZE: A REVIEW OF STATISTICAL THEORY Copyright © 2008 by Nelson, a division of Thomson Canada Limited Chapter 15 LEARNING OBJECTIVES What you will learn in this chapter 1. To discuss the purpose of inferential statistics by explaining the difference between population parameters and sample statistics 2. To make data usable by organizing and summarizing them into frequency distributions, proportions, and measurements of central tendency 3. To identify and calculate the various measures of central tendency and dispersion 4. To identify the characteristics of the normal distribution Copyright © 2008 by Nelson, a division of Thomson Canada Limited 15–1 LEARNING OBJECTIVES (cont’d) What you will learn in this chapter 5. To distinguish among population, sample, and sampling distributions and to identify the mean and standard deviation of each distribution 6. To compute confidence interval estimates 7. To understand the factors required for specifying sample size 8. To estimate the sample size for a simple random sample when the characteristic of interest is a mean and when it is a proportion 9. To understand which nonstatistical considerations influence the determination of sample size Copyright © 2008 by Nelson, a division of Thomson Canada Limited 15–2 Reviewing Basic Terminology • Descriptive and Inferential Statistics Descriptive statistics describe characteristics of populations or samples Inferential statistics is used to make inferences about a whole population from a sample • Sample Statistics and Population Parameters Sample statistics Variables in a sample or measures computed from sample data Population parameters Variables in a population or measured characteristics of the population Copyright © 2008 by Nelson, a division of Thomson Canada Limited 15–3 Making Data Usable • Frequency Distributions Frequency distribution A set of data organized by summarizing the number of times a particular value of a variable occurs Percentage distribution A frequency distribution organized into a table (or graph) that summarizes percentage values associated with particular values of a variable Probability The long-run relative frequency with which an event will occur Copyright © 2008 by Nelson, a division of Thomson Canada Limited 15–4 Making Data Usable (cont’d) • Proportions The percentage of elements that meet some criterion • Measures of Central Tendency The mean A measure of central tendency; the arithmetic average The median A measure of central tendency that is the midpoint; the value below which half the values in a distribution fall The mode A measure of central tendency; the value that occurs most often Copyright © 2008 by Nelson, a division of Thomson Canada Limited 15–5 Making Data Usable (cont’d) • Measures of Dispersion The range The distance between the smallest and the largest values of a frequency distribution Deviation scores A method of calculating how far any observation is from the mean Example: Copyright © 2008 by Nelson, a division of Thomson Canada Limited 15–6 Making Data Usable (cont’d) • Measures of Dispersion (cont’d) Why use the standard deviation? Variance: A measure of variability or dispersion. Its square root is the standard deviation Standard deviation: A quantitative index of a distribution’s spread, or variability; the square root of the variance for a distribution Copyright © 2008 by Nelson, a division of Thomson Canada Limited 15–7 The Normal Distribution • Normal Distribution A symmetrical, bell-shaped distribution that describes the expected probability distribution of many chance occurrences 99% of its values are within ± 3 standard deviations from its mean • Standardized Normal Distribution A purely theoretical probability distribution that reflects a specific normal curve for the standardized value, Z Copyright © 2008 by Nelson, a division of Thomson Canada Limited 15–8 Population Distribution, Sample Distribution, and Sampling Distribution • Population Distribution A frequency distribution of the elements of a population • Sample Distribution A frequency distribution of a sample • Sampling Distribution A theoretical probability distribution of sample means for all possible samples of a certain size drawn from a particular population Copyright © 2008 by Nelson, a division of Thomson Canada Limited 15–11 Population Distribution, Sample Distribution, and Sampling Distribution (cont’d) • Standard Error of the Mean The standard deviation of the sampling distribution Copyright © 2008 by Nelson, a division of Thomson Canada Limited 15–12 Central-Limit Theorem • Central-Limit Theorem The theory that, as sample size increases, the distribution of sample means of size n, randomly selected, approaches a normal distribution Copyright © 2008 by Nelson, a division of Thomson Canada Limited 15–13 Estimation of Parameters • Point Estimates An estimate of the population mean in the form of a single value, usually the sample mean Copyright © 2008 by Nelson, a division of Thomson Canada Limited 15–14 Estimation of Parameters (cont’d) • Confidence Intervals Confidence interval estimate A specified range of numbers within which a population mean is expected to lie; an estimate of the population mean based on the knowledge that it will be equal to the sample mean plus or minus a small sampling error Confidence level A percentage or decimal value that tells how confident a researcher can be about being correct. It states the long-run percentage of confidence intervals that will include the true population mean Copyright © 2008 by Nelson, a division of Thomson Canada Limited 15–15 Sample Size • Random Error and Sample Size Random sampling error varies with samples of different sizes Increasing the sample size decreases the width of the confidence interval at a given confidence level • Factors in Determining Sample Size for Questions Involving Means 1. The variance, or heterogeneity, of the population 2. The magnitude of acceptable error 3. The confidence level Copyright © 2008 by Nelson, a division of Thomson Canada Limited 15–16 Sample Size (cont’d) • Estimating Sample Size for Questions Involving Means Estimate the standard deviation of the population Make a judgment about the allowable magnitude of error Determine a confidence level Copyright © 2008 by Nelson, a division of Thomson Canada Limited 15–17 Sample Size (cont’d) • The Influence of Population Size on Sample Size In most cases the size of the population does not have a major effect on the sample size The variance of the population has the largest effect on sample size Copyright © 2008 by Nelson, a division of Thomson Canada Limited 15–18 Sample Size (cont’d) • Factors in Determining Sample Size for Proportions When the question involves the estimation of a proportion, the researcher requires some knowledge of the logic for determining a confidence interval around a sample proportion estimation of the population proportion Copyright © 2008 by Nelson, a division of Thomson Canada Limited 15–19 Sample Size (cont’d) • Calculating Sample Size for Sample Proportions In practice, a number of tables have been constructed for determining sample size • Determining Sample Size on the Basis of Judgment Just as sample units may be selected to suit the convenience or judgment of the researcher, sample size may also be determined on the basis of managerial judgments Copyright © 2008 by Nelson, a division of Thomson Canada Limited 15–20 Sample Size (cont’d) • Determining Sample Size for Stratified and Other Probability Samples Stratified sampling involves drawing separate probability samples within the subgroups to make the sample more efficient With a stratified sample the sample variances are expected to differ by strata Copyright © 2008 by Nelson, a division of Thomson Canada Limited 15–21 A Reminder About Statistics • Learning the terms and symbols defined in this chapter will provide you with the basics of the language of statisticians and researchers • As you learn more about the pragmatic use of statistics in marketing research, do not forget these concepts Copyright © 2008 by Nelson, a division of Thomson Canada Limited 15–22