First Course in Statistics

ISBN-10: 013014360X

ISBN-13: 9780130143600

Edition: 7th 2000

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This introduction to statistics helps readers develop and enhance their critical thinking skills. It shows readers how to analyze data that appear in situations in the world around them and features an abundance of examples and exercisesnearly all based on current, real-world applications pulled from journals, magazines, news articles, and commerce. In addition, this book exposes readers to the most recent statistical software packages that will prove helpful on the job. Presenting balanced coverage of both the theory and application of statistics, the book discusses methods for describing data sets; probability; random variables and probability distributions; inferences based on a single sample utilizing tests of hypothesis and confidence intervals; comparing population proportions and means; simple linear regression, and much more. For business, engineering, and science professionals.
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Book details

Edition: 7th
Copyright year: 2000
Publisher: Prentice Hall PTR
Binding: Hardcover
Pages: 539
Language: English

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
Graphic 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
Quartiles and Box Plots (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
Probability and Statistics: An Example
Random Sampling
Random Variables and Probability Distributions
Two Types of Random Variables
Probability Distributions for Discrete Random Variables
The Binomial Distribution
Probability Distributions for Continuous Random Variables
The Normal Distribution
Sampling Distributions
Properties of Sampling Distributions: Unbiasedness and Minimum Variance (Optional)
The Central Limit Theorem
Inferences Based on a Single Sample: Estimation with Confidence Intervals
Large-Sample Confidence Interval for a Population Mean
Small- Sample Confidence Interval for a Population Mean
Large-Sample Confidence Interval for a Population Proportion
Determining the Sample Size
Inferences Based on a Single Sample: Tests of Hypothesis
The Elements of a Test of Hypothesis
Large-Sample Test of Hypothesis About a Population Mean
Observed Significance Levels: p- Values
Small-Sample Test of Hypothesis About a Population Mean
Large-Sample Test of Hypothesis About a Population Proportion
A Nonparametric Test About a Population Median (Optional)
Comparing Population Means
Comparing Two Population Means: Independent Sampling
Comparing Two Population Means: Paired Difference Experiments
Determining the Sample Size
A Nonparametric Test for Comparing Two Populations: Independent Sampling (Optional)
A Nonparametric Test for Comparing Two Populations: Paired Difference Experiments (Optional)
Comparing Three or More Population Means: Analysis of Variance (Optional)
Comparing Population Proportions
Comparing Two Population Proportions: Independent Sampling
Determining the Sample Size
Comparing Population Proportions: Multinomial Experiment (Optional)
Contingency Table Analysis (Optional)
Simple Linear Regression
Probabilistic Models
Fitting the Model: The Least Squares Approach
Model Assumptions
An Estimator of �Ǡs2
Assessing the Utility of the Model: Making Inferences About the Slope �Ǡb1
The Coefficient of Correlation
The Coefficient of Determination
Using the Model for Estimation and Prediction
Simple Linear Regression: An Example
A Nonparametric Test for Correlation (Optional)
Data Sets
Calculation Formulas for Analysis of Variance: Independent Sampling
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