First Course in Statistics

ISBN-10: 0321891929

ISBN-13: 9780321891921

Edition: 11th 2013

List price: $196.00
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Description: Classic, yet contemporary. Theoretical, yet applied. McClave & Sincich’sStatisticsgives you the best of both worlds. This text offers a trusted, comprehensive introduction to statistics that emphasizes inference and integrates real data throughout. The authors stress the development of statistical thinking, the assessment of credibility, and value of the inferences made from data. TheTwelfth Editioninfuses a new focus on ethics, which is critically important when working with statistical data. Chapter Summaries have a new, study-oriented design, helping students stay focused when preparing for exams. Data, exercises, technology support, and Statistics in Action cases are updated throughout the book. 

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Book details

List price: $196.00
Edition: 11th
Copyright year: 2013
Publisher: Addison Wesley
Publication date: 8/10/2012
Binding: Mixed Media
Size: 8.50" wide x 11.00" long x 1.00" tall
Weight: 2.640
Language: English

James T. McClave, Info Tech, Inc./ University of Florida P. Goerge Benson, Terry College of Business, University of Georgia Terry Sincich, University of South Florida

Statistics, Data, and Statistical Thinking
the Science of Statistics
Types of Statistical Applications
Fundamental Elements of Statistics
Types of Data
Collecting Data
the Role of Statistics in Critical Thinking
Methods for Describing Sets of Data
Describing Qualitative Data
Graphical Methods for Describing Quantitative Data
Summation Notation
Numerical Measures of Central Tendency
Numerical Measures of Variability
Interpreting the Standard Deviation
Numerical Measures of Relative Standing
Methods for Detecting Outliers: Box Plots and z-Scores
Graphing Bivariate Relationships (Optional)
Distorting the Truth with Descriptive Techniques
Events, Sample Spaces, and Probability
Unions and Intersections
Complementary Events
the Additive Rule and Mutually Exclusive Events
Conditional Probability
the Multiplicative Rule and Independent Events
Random Sampling
Some Additional Counting Rules (Optional)
Bayes' Rule (Optional)
Random Variables and Probability Distributions
Two Types of Random Variables
Probability Distributions for Discrete Random Variables
Expected Values of Discrete Random Variables
the Binomial Random Variable
Continuous Probability Distributions
the Normal Distribution
Descriptive Methods for Assessing Normality
Approximating a Binomial Distribution with a Normal Distribution (Optional)
What is a Sampling Distribution?
the Sampling Distribution of (x-bar) and the Central Limit Theorem
Inferences Based on a Single Sample: Estimation with Confidence Intervals
Identifying and Estimating the Target Parameter
Confidence Interval for a Population Mean: Normal (z) Statistic
Confidence Interval for a Population Mean: Student's t-statistic
Large-Sample Confidence Interval for a Population Proportion
Determining the Sample Size
Confidence Interval for a Population Variance (Optional)
Inferences Based on a Single Sample: Tests of Hypothesis
the Elements of a Test of Hypothesis
Formulating Hypotheses and Setting Up the Rejection Region
Test of Hypothesis About a Population Mean: Normal (z) Statistic
Observed Significance Levels: p-Values
Test of Hypothesis About a Population Mean: Student's t-statistic
Large-Sample Test of Hypothesis About a Population Proportion
Calculating Type II Error Probabilities: More About � (Optional)
Test of Hypothesis About a Population Variance (Optional)
Single Population Inferences
Comparing Population Means
Identifying the Target Parameter
Comparing Two Population Means: Independent Sampling
Comparing Two Population Means: Paired Difference Experiments
Determining the Sample Size
the Completely Randomized Design: Single Factor
Comparing Two Populations: Independent Samples
Comparing Two Populations: Paired Difference Experiment
Comparing Population Proportions
Categorical Data and the Multinomial Distribution
Testing Categorical Probabilities: One-Way Table
Testing Categorical Probabilities: Two-Way (Contingency) Table
A Word of Caution About Chi-Square Tests
Comparing Two Population Proportions: Independent Sampling
Determining the Sample Size
Simple Linear Regression
Probabilistic Models
Fitting the Model: the Least Squares Approach
Model Assumptions
Assessing the Utility of the Model: Making Inferences About the Slope �1
the Coefficients of Correlation and Determination
Using the Model for Estimation and Prediction
A Complete Example
Rank Correlation
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