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An Introduction to Statistical Methods and Data Analysis

ISBN: 9780534931506 | 0534931502
Edition: 4th
Format: Paperback
Publisher: Duxbury Press
Pub. Date: 12/29/1998

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SummaryTable of Contents
This text teaches students to focus on basic statistical methods, the assumptions underlying the methods, and the interpretation and presentation of results of analyses. Integrating discussions of computer use and software packages within the content presentation, the text is especially suitable to those planning careers involving research/data analysis such as engineering, psychology, and biology.
PART 1 Introduction1(16)
What Is Statistics?
3(14)
Introduction
3(4)
... MORE
Why Study Statistics?
7(1)
Some Current Applications of Statistics
8(3)
What Do Statisticians Do?
11(1)
Quality and Process Improvement
12(3)
A Note to the Student
15(1)
Summary
15(2)
Supplementary Exercises
15(2)
PART 2 Gathering the Data17(22)
Using Surveys and Scientific Studies to Gather Data
19(20)
Introduction
19(1)
Surveys
20(5)
Scientific Studies
25(6)
Observational Studies
31(2)
Data Management: Preparing Data for Summarization and Analysis
33(3)
Summary
36(3)
PART 3 Summarizing Data39(82)
Data Description
41(80)
Introduction
41(1)
Describing Data on a Single Variable: Graphical Methods
42(25)
Describing Data on a Single Variable: Measures of Central Tendency
67(12)
Describing Data on a Single Variable: Measures of Variability
79(13)
Coding to Simplify Calculations (optional)
92(4)
The Box Plot
96(5)
Summarizing Data from More than One Variable
101(5)
Calculators, Computers, and Software Systems
106(1)
Summary
107(14)
Key Formulas
108(1)
Supplementary Exercises
109(12)
PART 4 Tools and Concepts121(74)
Probability and Probability Distributions
123(72)
How Probability Can Be Used in Making Inferences
123(3)
Finding the Probability of an Event
126(2)
Basic Event Relations and Probability Laws
128(3)
Conditional Probability and Independence
131(6)
Bayes's Formula
137(5)
Variables: Discrete and Continuous
142(2)
Probability Distributions for Discrete Random Variables
144(2)
A Useful Discrete Random Variable: The Binomial
146(13)
Probability Distributions for Continuous Random Variables
159(3)
A Useful Continuous Random Variable: The Normal Distribution
162(10)
Random Sampling
172(4)
The Sampling Distribution for y
176(10)
Normal Approximation to the Binomial
186(3)
Summary
189(6)
Key Formulas
190(1)
Supplementary Exercises
190(5)
PART 5 Analyzing Data: Means, Variances, and Proportions195(240)
Inferences About &mgr;
197(63)
Introduction
197(2)
Estimation of &mgr;
199(7)
Choosing the Sample Size for Estimating &mgr;
206(4)
Quality Control: y-charts
210(5)
A Statistical Test for &mgr;
215(11)
Choosing the Sample Size for Testing &mgr;
226(4)
The Level of Significance of a Statistical Test
230(4)
Inferences About &mgr;, &sgr; Unknown
234(12)
Summary
246(14)
Key Formulas
247(1)
Supplementary Exercises
248(12)
Inferences About &mgr;1 - &mgr;2
260(70)
Introduction
260(2)
Inferences about &mgr;1 - &mgr;2: Independent Samples
262(17)
A Nonparametric Alternative: The Wilcoxon Rank Sum Test
279(10)
A Quick, Portable Statistic: The Tukey-Duckworth Test (optional)
289(2)
Inferences About &mgr;1 - &mgr;2: Paired Data
291(6)
A Nonparametric Alternative: Wilcoxon Signed-Rank Test
297(6)
Choosing Sample Sizes for Inferences About &mgr;1 - &mgr;2
303(2)
Summary
305(25)
Key Formulas
306(2)
Supplementary Exercises
308(22)
Inferences About Population Variances
330(24)
Introduction
330(1)
Estimation and Tests for a Population Variance
330(7)
Quality Control: r-Charts and s-Charts
337(3)
Estimation and Tests for Comparing Two Population Variances
340(6)
Summary
346(8)
Key Formulas
347(1)
Supplementary Exercises
348(6)
Categorical Data
354(81)
Introduction
354(1)
The Multinomial Experiment and Chi-Square Goodness-of-Fit Test
354(11)
Inferences About the Binomial Parameter π
365(9)
Operating Characteristic Curves and Control Charts for &pgr; (optional)
374(6)
Comparing Two Binomial Proportions
380(7)
The Poisson Distribution
387(5)
r x c Contingency Tables: Chi-Square Test of Independence
392(10)
Measures of Association
402(5)
Combining Sets of r x c Contingency Tables (optional)
407(9)
Summary
416(19)
Key Formulas
416(2)
Supplementary Exercises
418(17)
PART 6 Analyzing Data: Regression Methods435(332)
Linear Regression and Correlation
437(54)
Introduction
437(4)
Linear Regression and the Method of Least Squares
441(10)
Quick, Portable Statistics (optional)
451(3)
Transformations to Linearize Data
454(6)
Correlation
460(10)
A Look Ahead: Multiple Regression
470(4)
Summary
474(17)
Key Formulas
475(1)
Supplementary Exercises
476(15)
Inferences Related to Linear Regression and Correlation
491(73)
Introduction
491(1)
Inferneces About β0 and β1
492(18)
Quick, Portable Statistics (optional)
510(4)
Inferneces Concerning E(y)
514(5)
Predicting y for a Given Value of x
519(6)
Examining Lack of Fit in Linear Regression
525(8)
The Calibration Problem: Predicting x for a Given Value of y
533(6)
Summary
539(25)
Key Formulas
540(3)
Supplementary Exercises
543(21)
Multiple Regression and the General Linear Model
564(83)
Introduction
564(9)
The General Linear Model
573(2)
Least Squares Solution to the General Linear Model
575(14)
Inferences About a Single Parameter in the General Linear Model
589(11)
Inferences Concerning E(y) and y
600(6)
Inferences concerning a Set of βs in a General Linear Model (optional)
606(8)
Matrix Notation for the General Linear Model (optional)
614(7)
Summary
621(26)
Formulas
622(1)
Supplementary Exercises
623(11)
Appendix: Matrix Operations
634(13)
More on Multiple Regression
647(120)
Introduction
647(1)
Selecting the Variables (step 1)
648(17)
Model Formulation (step 2)
665(27)
Residual Analysis: Checking Model Assumptions (step 3)
692(24)
Odds and Ends---Comparing the Slopes of Two or More Regression Lines
716(6)
Odds and Ends---Gencat: A General Linear Model Program for Categorical Data (optional)
722(11)
Summary
733(34)
Supplementary Exercises
733(34)
PART 7 Analyzing Data: Analysis of Variance Methods767(272)
Introduction to the Analysis of Variance
769(38)
Introduction
769(1)
The Logic Behind an Analysis f Variance
769(2)
A Statistical Test About More Than Two Population Means: An Analysis of Variance
771(12)
The Model for Observations in a Completely Randomized Design
783(2)
Checking on the Equal Variance Assumption
785(7)
A Nonparametric Alternative: The Kruskal-Wallis Test
792(4)
Summary
796(11)
Key Formulas
797(1)
Supplementary Exercises
798(9)
Multiple Comparisons
807(35)
Introduction
807(1)
Linear Contrasts
808(4)
Which Error Rate is Controlled?
812(1)
Fisher's Least Significant Difference
813(5)
Tukey's W Procedure
818(4)
Student-Newman-Keuls Procedure
822(3)
Duncan's New Multiple Range Test
825(3)
The k Ratio Rule for Making Pairwise Comparisons Among Treatment Means
828(5)
Scheffe's Method
833(3)
Summary
836(6)
Key Formulas
836(1)
Supplementary Exercises
837(5)
Analysis of Variance in Some Standard Experimental Designs
842(87)
Introduction
842(1)
Completely Randomized Design
843(1)
Randomized Block Design
844(15)
Latin Square Design
859(11)
Factorial Experiments
870(19)
Factorial Experiments Combined with Blocking Designs
889(2)
The Estimation of Treatment Differences and Multiple Comparisons
891(6)
Relationship Between Regression and Analysis of Variance (optional)
897(10)
Summary
907(22)
Key Formulas
907(2)
Supplementary Exercises
909(20)
Analysis of Variance for Some Unbalanced Designs
929(26)
Introduction
929(1)
A Randomized Block Design with One or More Missing Observations
930(7)
A Latin Square Design with Missing Data
937(4)
Incomplete Block Designs
941(6)
Summary
947(8)
Key Formulas
948(1)
Supplementary Exercises
949(6)
Analysis of Variance for Some Fixed-, Random-, and Mixed-Effects Models
955(44)
Introduction
955(2)
A One-Factor Experiment with Treatment Effects Random: A Random-Effects Model
957(5)
Extensions of Random-Effects Models
962(8)
Mixed-Effects Models
970(5)
Rules for Obtaining Expected Mean Squares
975(11)
Nested Sampling and the Split-Plot Design
986(9)
Summary
995(4)
Supplementary Exercises
996(3)
Experiments with Repeated Measures (Optional)
999(21)
Introduction
999(1)
Single-Factor Experiments with Repeated Measures
1000(3)
Two-Factor Experiments with Repeated Measures on One of the Factors
1003(7)
Crossover Designs
1010(4)
Summary
1014(6)
Supplementary Exercises
1014(6)
The Analysis of Covariance
1020(19)
Introduction
1020(1)
A Completely Randomized Design with One Covariate
1020(11)
The Extrapolation Problem
1031(3)
Multiple Covariates and More Complicated Designs
1034(3)
Summary
1037(2)
Supplementary Exercises
1037(2)
PART 8 Communicating and Documenting the Results of Analyses1039(2)
Communicating and Documenting the Results of Analyses
1041(1)
Introduction
1041(1)
The Difficulty of Good Communication
1041(2)
Communication Hurdles: Graphical Distortions
1043(2)
Communication Hurdles: Biased Samples
1045(1)
Communication Hurdles: Sample Size
1046(1)
The Statistical Report
1047(2)
Documentation and Storage of Results
1049(2)
Summary
1051(1)
Supplementary Exercises
1051
Appendix A: Statistical TablesA-1
Appendix B: Clinical Trial Data BaseA-39
ReferencesA-45
AnswersA-53
IndexA-121

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