Book contents
- Frontmatter
- Contents
- Preface
- 1 Introduction to statistics
- 2 Frequency distributions and graphs
- 3 Descriptive statistics: measures of central tendency and dispersion
- 4 Probability and statistics
- 5 Hypothesis testing
- 6 The difference between two means
- 7 Analysis of variance (ANOVA)
- 8 Non-parametric comparison of samples
- 9 Simple linear regression
- 10 Correlation analysis
- 11 The analysis of frequencies
- References
- Appendix A Answers to selected exercises
- Appendix B A brief overview of SAS/ASSIST
- Appendix C Statistical tables
- Index
11 - The analysis of frequencies
Published online by Cambridge University Press: 05 June 2012
- Frontmatter
- Contents
- Preface
- 1 Introduction to statistics
- 2 Frequency distributions and graphs
- 3 Descriptive statistics: measures of central tendency and dispersion
- 4 Probability and statistics
- 5 Hypothesis testing
- 6 The difference between two means
- 7 Analysis of variance (ANOVA)
- 8 Non-parametric comparison of samples
- 9 Simple linear regression
- 10 Correlation analysis
- 11 The analysis of frequencies
- References
- Appendix A Answers to selected exercises
- Appendix B A brief overview of SAS/ASSIST
- Appendix C Statistical tables
- Index
Summary
This chapter presents a departure from the statistical tests covered so far: we do not deal with quantitative variables such as fertility, prestige ranks, height, weight, etc., within a sample or among several samples. Here we deal with frequencies of occurrences or events. We work with one variable which has a few possible outcomes, and are concerned with the number of individuals who have each of the outcomes (where a is the number of outcomes). Often-used anthropological frequency data are gene frequencies, the frequencies of males and females, the frequencies of different ethnic groups, the frequencies of different pottery styles in archaeological sites, etc.
This chapter covers the well-known and widely used chi-square test (X2), applied as a goodness-of-fit test and as a test for independence of two variables. Not only is the X2 test widely used, but unfortunately it has also been widely misused. Therefore, a correction which must be applied to small data sets is also discussed. The most common error about the X2 test is its own name: it is not infrequently referred to as X2, which is the parametric notation for a theoretical frequency distribution against which the statistic computed from the sample (X2) should be compared.
The X2 test for goodness-of-fit
The purpose of this test is to determine if the observed frequencies of events depart significantly from frequencies proposed by a null hypothesis.
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- Chapter
- Information
- Statistics for Anthropology , pp. 192 - 203Publisher: Cambridge University PressPrint publication year: 1998