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Introductory Statistics
This text follows scope and sequence requirements of a one-semester introduction to statistics course and is geared toward students majoring in fields other than math or engineering. The text assumes some knowledge of intermediate algebra and focuses on statistics application over theory. Introductory Statistics includes innovative practical applications that make the text relevant and accessible, as well as collaborative exercises, technology integration problems, and statistics labs.
- Author
- Barbara Illowsky & Susan Dean
- Publisher
- De Anza College
- Source
- LibreTexts
- License
- CC BY
- Language
- EN
- Category
- Basic Sciences
Contents· 75 sections
- 01: Sampling and Data
- 1.01: Introduction to Probability and Statistics
- 1.02: Key Terms and Definitions
- 1.03: Populations and Samples
- 02: Descriptive Statistics
- 2.01: Organizing and Graphing Qualitative Data
- 2.02: Organizing and Graphing Quantitative Data
- 2.03: Stem-and-Leaf Displays
- 2.04: Measures of Central Tendency- Mean Median and Mode
- 2.05: Measures of Position- Percentiles and Quartiles
- 2.06: Box Plots
- 2.07: Measures of Spread- Variance and Standard Deviation
- 2.08: Skewness and the Mean Median and Mode
- 03: Introduction to Linear Regression and Correlation
- 3.01: Linear Equations
- 3.02: Scatter Plots
- 3.03: Simple Linear Regression
- 3.04: Prediction
- 3.05: Outliers
- 04: Probability Theory
- 4.01: Probability Experiments and Sample Spaces
- 4.02: Experiments Having Equally Likely Outcomes
- 4.03: Conditional Probability and Independence
- 4.04: Counting Basics- the Multiplication and Addition Rules
- 4.05: Intersection and Union of Events and Venn Diagrams
- 4.06: Joint and Marginal Probabilities and Contingency Tables
- 4.07: More Counting- Factorials Combinations and Permutations
- 05: Discrete Random Variables
- 5.01: Introduction to Random Variables
- 5.02: The Probability Distribution Function
- 5.03: Expectation Variance and Standard Deviation
- 5.04: The Binomial Distribution
- 5.05: The Geometric Distribution
- 5.06: The Hypergeometric Distribution
- 5.07: The Poisson Distribution
- 06: Continuous Random Variables
- 6.01: Probability Density Functions
- 6.02: The Uniform and Other Simple Continuous Distributions
- 6.03: The Standard Normal Distribution
- 6.04: Applications of Finding Normal Probabilities
- 07: Sampling Distributions
- 7.01: The Sample Mean and Sources of Error
- 7.02: The Sum Distribution
- 08: Confidence Intervals
- 8.01: Estimating Population Means
- 8.02: The t-distribution
- 8.03: Estimating Proportions
- 8.04: Confidence Intervals
- 09: Hypothesis Testing for a Single Variable and Population
- 9.01: Hypothesis Tests- An Introduction
- 9.02: Type I and Type II Errors
- 9.03: Hypothesis Tests about - p-value Approach
- 9.04: Hypothesis Tests about - Critical Region Approach
- 9.05: Hypothesis Tests for a Proportion
- 10: Hypothesis Testing for Paired and Unpaired Data
- 10.01: Two Population Means
- 10.02: Two Independent Population Proportions
- 10.03: Matched or Paired Samples
- 10.04: Two Population Means with Known Standard Deviations
- 10.05: Difference of Two Means
- 11: Linear Regression and Hypothesis Testing
- 11.01: Testing the Hypothesis that 0
- 12: The Chi-Square Distribution
- 12.01: The Chi-Square Distribution
- 12.02: A Goodness-of-Fit Test
- 12.03: A Test of Independence or Homogeneity
- 12.04: Test of a Single Variance
- 12.05: Test for Homogeneity
- 12.06: Comparison of the Chi-Square Tests
- 13: F Distribution and One-Way ANOVA
- 13.01: Prelude to F Distribution and One-Way ANOVA
- 13.02: One-Way ANOVA
- 13.03: The F Distribution and the F-Ratio
- 13.04: Facts About the F Distribution
- 13.05: Test of Two Variances