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THINKING STATISTICALLY: ELEPHANTS GO TO SCHOOL [Pehme köide]

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  • Formaat: Paperback / softback, 672 pages
  • Ilmumisaeg: 23-Jan-2007
  • Kirjastus: Kendall/Hunt Publishing Co ,U.S.
  • ISBN-10: 0757540473
  • ISBN-13: 9780757540479
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THINKING STATISTICALLY: ELEPHANTS GO TO SCHOOLSuurem pilt
  • Formaat: Paperback / softback, 672 pages
  • Ilmumisaeg: 23-Jan-2007
  • Kirjastus: Kendall/Hunt Publishing Co ,U.S.
  • ISBN-10: 0757540473
  • ISBN-13: 9780757540479
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9780757540479.html
Dedication iii
Foreword v
David Robinson
Foreword viii
Stephen Horn
Preface xii
1 Basic Concepts
1.1 Introduction
1(1)
1.2 What is statistics?
1(1)
1.3 Definition of statistics
1(6)
1.3.1 Population
2(3)
1.3.2 Sample
5(1)
1.3.2.1 Random sample
6(1)
1.3.2.2 Representative sample
6(1)
1.4 Population size
7(1)
1.5 Sample size
7(1)
1.6 Simple random sampling
7(9)
1.6.1 Lottery method
7(6)
1.6.2 Random numbers table method
13(3)
1.7 Parameter
16(1)
1.8 Statistic
16(3)
1.9 Bias and its sources
19(2)
1.9.1 Selection bias
19(1)
1.9.1.1 Convenience sample
19(1)
1.9.1.2 Volunteer sample
20(1)
1.9.2 Other sources of bias
20(1)
1.9.2.1 Non-response
20(1)
1.9.2.2 False response
21(1)
1.10 Probability sampling
21(15)
1.10.1 Stratified sampling
22(1)
1.10.2 Systematic sampling
23(1)
1.10.3 Cluster sampling
24(2)
1.10.4 Multi-stage sampling
26(10)
1.11 Proportion
36(2)
1.12 Estimate of total in stratified random sampling
38(3)
1.13 Proportion in stratified random sampling
41(3)
1.14 Hypotheses
44(6)
1.14.1 Significance level
47(1)
1.14.2 Decision rule
47(3)
1.15 Some secrets of statistics
50(35)
1.15.1 Scope of statistics
50(1)
1.15.2 Limitations of statistics
50(1)
1.15.3 Lack of confidence in statistics
50(1)
Let Us Do It
51(34)
2 Statistical Studies
2.1 Introduction
85(1)
2.2 Unit
85(1)
2.3 Experimental and observational studies
86(8)
2.4 Randomized block design
94(1)
2.5 Completely randomized design
95(4)
2.6 Survival analysis
99(3)
2.6.1 Event
99(1)
2.6.2 Time
99(1)
2.6.3 Censored data
99(2)
2.6.4 Survival data storage
101(1)
2.7 Human blood types
102(9)
Let Us Do It
104(7)
3 Graphical Representation
3.1 Introduction
111(1)
3.2 Qualitative random variables
111(1)
3.2.1 Nominal variables
112(1)
3.2.2 Ordinal variables
112(1)
3.3 Quantitative random variables
112(3)
3.3.1 Discrete random variables
112(1)
3.3.2 Continuous random variables
113(2)
3.4 Graphs for qualitative data
115(3)
3.4.1 Pie chart
115(1)
3.4.2 Bar chart
115(3)
3.5 Raw data
118(1)
3.6 Frequency distribution table for a qualitative variable
118(3)
3.6.1 Pareto chart
119(2)
3.7 Graphs for quantitative data
121(15)
3.7.1 Pie chart
123(1)
3.7.2 Bar chart
123(2)
3.7.3 Dot plot
125(3)
3.7.4 Line plot
128(3)
3.7.5 Stem and leaf plot
131(5)
3.8 Histogram
136(37)
3.8.1 Tools for making histogram
136(1)
3.8.1.1 Frequency distribution
136(1)
3.8.1.2 Class boundaries
137(1)
3.8.1.3 Class width
137(1)
3.8.1.4 Class midpoint
138(1)
3.8.1.5 Steps to make a frequency distribution
138(7)
Let Us Do It
145(28)
4 Numerical Representation
4.1 Introduction
173(1)
4.2 Meaning of 2
173(2)
4.3 Central value of a data set
175(1)
4.4 Population mean
175(1)
4.5 Sample mean
176(3)
4.6 Outliers
179(1)
4.7 Effect of outliers on the sample mean
179(2)
4.8 Median
181(3)
4.8.1 Rules to find sample median
181(2)
4.8.2 Effect of outliers on median
183(1)
4.9 Mode
184(1)
4.10 Positions of mean, median, and mode
185(6)
4.10.1 Multi-modal data sets
187(4)
4.11 Idea of spread of data
191(2)
4.12 Range
193(1)
4.13 Mean absolute deviation
194(2)
4.14 Variance
196(3)
4.14.1 Population variance
196(1)
4.14.1.1 Population standard deviation
196(2)
4.14.2 Sample variance
198(1)
4.14.2.1 Sample standard deviation
198(1)
4.15 Coefficient of variation
199(9)
4.16 Tchebysheff's rule
208(3)
4.17 Empirical rule
211(8)
4.18 Relative standing
219(7)
4.18.1 Z-score
219(3)
4.18.2 Quartiles
222(1)
4.18.3 Interquartile range
223(3)
4.19 Box plot
226(51)
4.19.1 Use of a box plot
227(1)
4.19.2 Steps to make a box plot
227(1)
4.19.3 Detection of outliers using a box plot
228(1)
4.19.4 Seven measures for a box plot
229(20)
Let Us Do It
249(28)
5 Touching Probability
5.1 Introduction
277(1)
5.2 Experiment
277(1)
5.3 Event
278(1)
5.4 Mutually exclusive events
279(1)
5.5 Compound events
279(1)
5.6 Simple events
279(1)
5.7 Sample space
280(1)
5.8 Tree diagram
280(6)
5.9 Venn diagram
286(1)
5.10 Null event
286(1)
5.11 Sure event
286(1)
5.12 Intersection of events
286(2)
5.13 Union of events
288(1)
5.14 Complement of an event
289(1)
5.15 Definition of probability
289(1)
5.16 Probability of an event
290(4)
5.16.1 Steps to find the probability of an event
290(4)
5.17 Marginal and conditional probabilities
294(5)
5.17.1 Marginal probability
295(1)
5.17.2 Conditional probability
296(2)
5.17.3 Independent events
298(1)
5.18 Mathematical laws of probability
299(23)
5.19 Mixing colors
322(2)
5.20 Idea of simulating probabilities
324(39)
Let Us Do It
329(34)
6 Discrete Distributions
6.1 Introduction
363(1)
6.2 Discrete random variable
363(1)
6.3 Discrete probability distribution
363(10)
6.3.1 Mean value of a discrete random variable
364(1)
6.3.2 Variance of a discrete random variable
365(1)
6.3.3 Standard deviation of a discrete random variable
365(8)
6.4 Binomial distribution
373(17)
6.4.1 Binomial experiment
374(1)
6.4.2 Mean and variance of the binomial variable
374(16)
6.5 Poisson distribution
390(15)
Let Us Do It
393(12)
7 Continuous Distributions
7.1 Introduction
405(1)
7.2 Continuous random variable
405(1)
7.3 Probability density function
405(2)
7.4 Uniform distribution
407(8)
7.5 Normal distribution
415(36)
7.5.1 Population Z-score
416(19)
7.5.2 Detection of outliers with Z-score
435(1)
7.5.3 How to generate a normal distribution?
436(3)
Let Us Do It
439(12)
8 Sampling Distributions
8.1 Introduction
451(1)
8.2 Sampling distribution of a statistic
451(1)
8.3 Sampling distribution of sample mean
451(5)
8.3.1 Some important results
455(1)
8.4 Sampling distribution of sample proportion
456(4)
8.4.1 Some important results
460(1)
8.5 Unbiasedness
460(1)
8.6 Standard deviation and standard error of a statistic
461(2)
8.7 Central limit theorem
463(1)
8.8 Point estimate and estimator
463(1)
8.9 Interval estimate and estimator
464(1)
8.10 Large sample confidence interval estimate and estimator
464(8)
8.10.1 Population mean
464(1)
8.10.2 Population proportion
465(7)
8.11 Small sample size confidence interval estimate and estimator
472(4)
8.11.1 Small sample size confidence interval estimator for a single population mean
473(3)
8.12 Confidence interval estimator for the difference between two means
476(3)
8.12.1 Large sample size
476(1)
8.12.2 Small sample size
477(2)
8.13 Confidence interval estimator for the difference between two proportions
479(2)
8.14 Some important results
481(8)
Let Us Do It
482(7)
9 The Idea of Hypotheses Testing
9.1 Introduction
489(1)
9.2 The need of hypotheses testing
489(3)
9.3 Significance level
492(1)
9.4 Decision rule
492(1)
9.5 Rejection region
492(1)
9.6 Acceptance region
493(1)
9.7 Critical value
493(1)
9.8 Large sample test for single proportion
493(6)
9.9 Large sample test for single mean
499(7)
9.10 Idea of p-value using Z-score
506(3)
9.10.1 p-value for left-tailed test using Z-score
506(1)
9.10.2 p-value for right-tailed test using Z-score
507(1)
9.10.3 p-value for two-tailed test using Z-score
508(1)
9.11 Small sample test for single mean
509(8)
9.12 Large sample test for the difference between two means
517(4)
9.13 Small sample test for the difference between two population means for independent random samples
521(8)
9.14 Small sample test for the difference between two means for two dependent samples (Paired t-test)
529(5)
9.15 Idea of p-value using t-score
534(4)
9.15.1 p-value for left-tailed test using t-score
534(2)
9.15.2 p-value for right-tailed test using t-score
536(1)
9.15.3 p-value for two-tailed test using t-score
537(1)
9.16 Large sample test for the difference between two proportions
538(4)
9.17 Contingency table and the chi-square test
542(9)
9.17.1 Equivalency of chi-square test and Z-test
547(4)
9.18 Chi-square test for single variance
551(4)
9.19 F-test for two population variances
555(4)
9.20 Analysis of variance (ANOVA)
559(28)
Let Us Do It
564(23)
10 Analyzing Bivariate Data
10.1 Introduction
587(1)
10.2 Bivariate data
587(1)
10.3 Correlation analysis
587(12)
10.3.1 Graphical method: Scatter plot
588(2)
10.3.2 Numerical method: Pearson's correlation coefficient
590(1)
10.3.3 Properties of the correlation coefficient
590(9)
10.4 Regression analysis
599(12)
10.4.1 Some facts about the best fit line
603(8)
10.5 Relation between Z-score and the correlation coefficient
611(1)
10.6 Relation between correlation and regression coefficients
612(6)
10.7 Advanced rules of mean, variance, and standard deviation
618(19)
10.7.1 Rules of mean
618(1)
10.7.2 Rules of variance
618(1)
10.7.3 Rules of standard deviation
619(1)
Let Us Do It
620(17)
USEFUL STATISTICAL TABLES
Pseudo Random Numbers
637(1)
Area under the standard normal curve
638(2)
Critical values for t-score
640(1)
Chi-square critical values, X2c = X2α (df)
641(1)
F-ratios at 5% level of significance
642(1)
Important Formulae 643(4)
Bibliography 647(2)
Handy Subject Index 649