First Course in Statistical Methods

ISBN-10: 0534408060
ISBN-13: 9780534408060
Edition: 2004
List price: $333.95 Buy it from $95.38
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Description: A FIRST COURSE IN STATISTICAL METHODS addresses a pressing need in the methods course?a shorter text designed for a one-term course. By selecting and revising material from their best-selling two-semester text, AN INTRODUCTION TO STATISTICAL METHODS  More...

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Book details

List price: $333.95
Copyright year: 2004
Publisher: Brooks/Cole
Publication date: 7/30/2003
Binding: Hardcover
Pages: 768
Size: 8.00" wide x 10.00" long x 1.25" tall
Weight: 3.674
Language: English

A FIRST COURSE IN STATISTICAL METHODS addresses a pressing need in the methods course?a shorter text designed for a one-term course. By selecting and revising material from their best-selling two-semester text, AN INTRODUCTION TO STATISTICAL METHODS AND DATA ANALYSIS, Fifth Edition, the authors created an ideal book for a one-term course in statistical methods. Based on the belief that statistics is a thought process tied to the scientific method, the text utilizes a 5-step approach: 1) defining the problem, 2) collecting data, 3) summarizing data, 4) analyzing and interpreting the data, and 5) communicating the results of the analysis.

Defining The Problem
Statistics and the Scientific Method
Introduction
Why Study Statistics? Some Current Applications of Statistics
A Note to the Student
Staying Focused
Collecting Data
Collecting Data Using Surveys and Scientific Studies
Introduction
Surveys
Sampling Designs for Surveys
Scientific Studies
Experimental Designs for Scientific Studies
Observational Studies
Data Management: Preparing Data for Summarization and Analysis (Optional)
Staying Focused
Summarizing Data
Summarizing Data
Introduction
Calculators, Computers, and Software Systems
Summarizing Data on a Single Variable: Graphical Methods
Summarizing Data on a Single Variable: Measures of Central Tendency
Summarizing Data on a Single Variable: Measures of Variability
The Boxplot
Summarizing Data from More than One Variable
Encounters with Real Data
Staying Focused
Probability and Probability Distributions
How Probability Can Be Used in Making Inferences
Finding the Probability of an Event
Basic Event Relations and Probability Laws
Conditional Probability and Independence
Bayes+ Formula
Variables: Discrete and Continuous
Probability Distributions for Discrete Random Variables
A Useful Discrete Random Variable: The Binomial
Probability Distributions for Continuous Random Variables
A Useful Continuous Random Variable: The Normal Distribution
Random Sampling
Sampling Distributions
Normal Approximation to the Binomial
MINITAB Instructions (Optional)
Staying Focused
Analyzing Data, Interpreting The Analyses, And Communicating The Results
Inferences About Population Central Values
Introduction
Estimation of 8
Choosing the Sample Size for Estimating 8
A Statistical Test for 8
Choosing the Sample Size for Testing 8
The Level of Significance of a Statistical Test
Inferences about 8 for Normal Population, = Unknown
Inferences about Median
Encounters with Real Data
Staying Focused
Inferences Comparing Two Population Central Values
Introduction
Inferences about 81+82: Independent Samples
A Nonparametric Alternative: The Wilcoxon Rank Sum Test
Inferences about 81+82: Paired Data
A Nonparametric Alternative: The Wilcoxon Signed-Rank Test
Choosing Sample Sizes for Inferences about 81+82
Encounters with Real Data
Staying Focused
Inferences About Population Variances
Introduction
Estimation and Tests for a Population Variance
Estimation and Tests for Comparing Two Population Variances
Tests for Comparing t >2 Population Variances
Encounters with Real Data
Staying Focused
The Completely Randomized Design
Introduction
The Model for Observations in a Completely Randomized Design
Analyzing Data from a Completely Randomized Design: An Analysis of Variances
Checking on the AOV Conditions
A Nonparametric Alternative: The Kruskal+Wallis Test
Multiple Comparisons
Encounters with Real Data
Staying Focused
More Complicated Experimental Designs
Introduction
Randomized Complete Block Design
Latin Square Design
Factorial Treatment Structure in a Completely Randomized Design
Factorial Treatment Structure in a Randomized Complete Block Design
Estimation of Treatment Differences and Comparisons of Treatment Means
Encounters with Real Data
Staying Focused
Categorical Data
Introduction
Inferences About a Population Proportion =.Inferences About the Difference Between Two Population Proportions =1+ =2
Inferences About Several Proportions: Chi-Square Goodness-of-Fit Test
Contingency Tables: Tests for Independence and Homogeneity
Odds and Odds Ratios
Encounters with Real Data
Staying Focused
Linear Regression and Correlation
Introduction
Estimating Model Parameters
Inferences about Regression Parameters
Predicting New y Values Using Regression
Examining Lack of Fit in Linear Regression
The Inverse Regression Problem (Calibration)
Correlation
Encounters with Real Data
Staying Focused
Multiple Regression
Introduction
Est

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