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Statistics for Anthropology [Kõva köide]

(University of South Florida)
  • Formaat: Hardback, 252 pages, kõrgus x laius x paksus: 254x179x23 mm, kaal: 655 g, 12 Tables, unspecified; 1 Halftones, unspecified; 37 Line drawings, unspecified
  • Ilmumisaeg: 23-Apr-1998
  • Kirjastus: Cambridge University Press
  • ISBN-10: 0521571162
  • ISBN-13: 9780521571166
Teised raamatud teemal:
  • Formaat: Hardback, 252 pages, kõrgus x laius x paksus: 254x179x23 mm, kaal: 655 g, 12 Tables, unspecified; 1 Halftones, unspecified; 37 Line drawings, unspecified
  • Ilmumisaeg: 23-Apr-1998
  • Kirjastus: Cambridge University Press
  • ISBN-10: 0521571162
  • ISBN-13: 9780521571166
Teised raamatud teemal:
"Anthropology as a discipline is rapidly becoming more quantitative, and anthropology students are now required to develop sophisticated statistical skills. This book provides students of anthropology with a clear, step-by-step guide to univariate statistical methods, demystifying the aspects that are often seen as difficult or impenetrable. Explaining the central role of statistical methods in anthropology, and using only anthropological examples, the book provides a solid footing in statistical techniques. Beginning with basic descriptive statistics, this new edition also covers more advanced methods such as analyses of frequencies and variance, and simple and multiple regression analysis with dummy and continuous variables. It addresses commonly encountered problems such as small samples and non-normality. Each statistical technique is accompanied by clearly worked examples, and the chapters end with practice problem sets"--

A step-by-step introduction to basic statistics for students of anthropology and social science.

Anthropology students increasingly need a quantitative background, but statistics are often seen as too difficult. Statistics for Anthropology offers students of anthropology and other social sciences an easy, step-by-step route through the statistical maze. In clear, simple language, and using relevant examples and practice problems, this guide provides a solid footing in basic statistical techniques. It is designed to give students a thorough grounding in methodology, and also insight into how and when to apply the various processes. The book assumes a minimal background in mathematics, and is suitable for the computer-literate and -illiterate. Although only a hand calculator is needed, computer statistical software can be used to accompany the text. This book will be an essential resource for all anthropology and social science students seeking an introduction to basic statistics.

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A step-by-step introduction to basic statistics for students of anthropology and social science.
Preface xiii
1 Introduction to statistics
1(14)
1.1 Statistics and scientific inquiry
1(2)
1.2 Basic definitions
3(7)
1.2.1 Validity and reliability
3(1)
1.2.2 Variables and constants
4(1)
1.2.3 Independent and dependent variables
5(1)
1.2.4 Control and experimental groups
6(1)
1.2.5 Scales of measurement and variables
6(2)
1.2.6 Samples and statistics, populations and parameters; descriptive and inferential statistics; a few words about sampling
8(2)
1.3 Statistical notation
10(2)
1.4 Rounding-off rules
12(1)
1.5 Key concepts
13(1)
1.6 Exercises
13(2)
2 Frequency distributions and graphs
15(16)
2.1 Frequency distributions of qualitative variables
15(3)
2.2 Frequency distributions of numerical discontinuous variables
18(2)
2.3 Frequency distributions of continuous numerical variables
20(5)
2.4 Graphs
25(3)
2.4.1 Bar graphs
25(2)
2.4.2 Pie charts
27(1)
2.4.3 Histograms
27(1)
2.4.4 Polygons
28(1)
2.5 Key concepts
28(1)
2.6 Exercises
29(2)
3 Descriptive statistics: measures of central tendency and dispersion
31(23)
3.1 Measures of central tendency
31(9)
3.1.1 The Mean
31(2)
3.1.2 Computing the mean of frequency distributions
33(1)
3.1.3 The median
34(1)
3.1.4 Computing the median of frequency distributions
35(4)
3.1.5 The mode
39(1)
3.2 Measures of variation
40(11)
3.2.1 The range
40(1)
3.2.2 The population variance and standard deviation; the definitional formulae
41(2)
3.2.3 The sample variance and standard deviation; the definitional formulae
43(2)
3.2.4 The population and sample variance and standard deviation; the computational (`machine') formula
45(2)
3.2.5 The computational (`machine') formula with frequency distributions
47(4)
3.3 A research example of descriptive statistics
51(1)
3.4 Key concepts
52(1)
3.5 Exercises
52(2)
4 Probability and statistics
54(23)
4.1 Random sampling and probability distributions
54(1)
4.2 The probability distribution of qualitative and discontinuous numerical variables
55(2)
4.3 The binomial distribution
57(3)
4.4 The probability distribution of continuous variables
60(9)
4.4.1 z scores
64(4)
4.4.2 Percentile ranks and percentiles
68(1)
4.5 The probability distribution of sample means
69(4)
4.6 A research example of z scores
73(1)
4.7 Key concepts
74(1)
4.8 Exercises
74(3)
5 Hypothesis testing
77(19)
5.1 The principles of hypothesis testing
77(4)
5.2 Errors and power in hypothesis testing
81(4)
5.2.1 Type I error (Alpha)
81(1)
5.2.2 Type II error (Beta)
82(1)
5.2.3 Power of statistical tests (1-Beta)
83(2)
5.3 Examples of hypothesis tests using z scores
85(2)
5.4 One- and two-tail hypothesis tests
87(2)
5.5 Assumptions of statistical tests
89(1)
5.6 Hypothesis testing with the t distribution
90(2)
5.7 Examples of hypothesis tests with t scores
92(2)
5.8 Reporting hypothesis tests
94(1)
5.9 Key concepts
95(1)
5.10 Exercises
95(1)
6 The difference between two means
96(17)
6.1 The un-paired t test
96(4)
6.2 Assumptions of the un-paired t test
100(3)
6.3 A research example of the un-paired t test
103(1)
6.4 The comparison of a single observation with the mean of a sample
104(1)
6.5 The comparison of paired samples
105(2)
6.6 Assumptions of the paired t test
107(2)
6.7 A research example of the paired t test
109(1)
6.8 Key concepts
109(1)
6.9 Exercises
109(4)
7 Analysis of variance (ANOVA)
113(17)
7.1 One-way ANOVA
113(1)
7.2 ANOVA procedure and nomenclature
114(7)
7.3 ANOVA assumptions
121(1)
7.4 Post ANOVA comparison of means
121(5)
7.4.1 The Scheffe test
122(4)
7.5 A research example of an ANOVA
126(1)
7.6 Key concepts
127(1)
7.7 Exercises
127(3)
8 Non-parametric comparison of samples
130(21)
8.1 Ranking data
131(1)
8.2 The Mann-Whitney U test for an un-matched design
132(5)
8.3 A research example of the Mann-Whitney U test
137(1)
8.4 The Kruskal-Wallis instead of a one-way, model I ANOVA
138(6)
8.5 A research example of the Kruskal-Wallis test
144(1)
8.6 The Wilcoxon signed-rank test for a paired design
144(3)
8.7 A research example of the use of the Wilcoxon signed-rank test
147(1)
8.8 Key concepts
148(1)
8.9 Exercises
148(3)
9 Simple linear regression
151(28)
9.1 An overview of regression analysis
152(4)
9.2 Plot and inspection of the data
156(1)
9.3 Description of the relation between X and Y with an equation
156(2)
9.4 Expression of the regression analysis as an analysis of variance of Y
158(3)
9.5 Test of the null hypothesis H0: Beta=0
161(1)
9.6 Use of the regression equation to predict values of Y
161(4)
9.7 Residual analysis
165(10)
9.8 A research example of the use of regression
175(1)
9.9 Key concepts
176(1)
9.10 Exercises
176(3)
10 Correlation analysis
179(13)
10.1 The Pearson product-moment correlation
179(6)
10.2 A research example of the use of Pearson correlation
185(1)
10.3 The Spearman correlation
185(4)
10.4 A research example of the Spearman correlation coefficient
189(1)
10.5 Key concepts
190(1)
10.6 Exercises
190(2)
11 The analysis of frequencies
192(12)
11.1 The X^2 test for goodness-of-fit
192(3)
11.2 A research example of the X^2 test for goodness-of-fit
195(1)
11.3 The X^2 test for independence of variables
196(4)
11.4 A research example of the X^2 test for independence of variables
200(1)
11.5 Yates' correction for continuity
200(2)
11.6 Key concepts
202(1)
11.7 Exercises
203(1)
References 204(3)
Appendix A: Answers to selected exercises 207(9)
Appendix B: A brief overview of SAS/ASSIST 216(3)
Appendix C: Statistical tables 219(18)
Table
1. The unit normal table
219(3)
Table
2. Critical values of the t distribution
222(1)
Table
3. Upper 5 and 1% points of the maximum F-ratio
223(1)
Table
4. Critical values of the F distribution
224(4)
Table
5. Critical values of U, the Mann-Whitney statistic
228(4)
Table
6. Critical values of the chi-square distribution
232(2)
Table
7. Critical values of T for the Wilcoxon signed-rank test
234(1)
Table
8. Critical values of the Pearson correlation coefficient r
235(2)
Index 237