Statistics Alive - Steinberg, Wendy J.

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Résumé :
Statistics need not be dull and dry! Presented in short, digestible modules and written in a conversational tone, with anecdotal stories and light-hearted humour, this text is an enjoyable read. Students are shown the underlying logic to what they're learning, and well-crafted practice and self-check features help ensure that that new knowledge sticks. Coverage of probability theory and mathematical proofs is minimized without sacrificing the rigour of the text, and more advanced concepts are introduced at the end of the book for instructors wishing to challenge students or use the text in a more advanced course.

Key Features:

- The Lay-flat Paperback Format makes doing assignments from the book easier for the student.

- Text content is presented in Short Modules allowing students to digest subject matter in manageable chunks and allowing instructors more flexibility in the assignment of material.

- Learning Objectives and Check Yourself! Questions provide guideposts that students can use to orient themselves and assess their readiness to move on and tackle new material.

- Practice Exercises dispersed throughout the text, in the student study guide, and online provide students with ample opportunity to master concepts and formulae...

Sommaire:
List of Figures
List of Tables
Preface
Supplemental Material for Use With Statistics Alive!
Acknowledgments
Part I. Preliminary Information: First Things First
1. Math Review, Vocabulary, and Symbols
Getting Started
Vocabulary and Symbols
Some Rules and Procedures
More Rules and Procedures
2. Measurement Scales
What Is Measurement?
Scales of Measurement
Continuous Versus Discrete Variables
Real Limits
Part II. Tables and Graphs: On Display
3. Frequency and Percentile Tables
Why Use Tables?
Frequency Tables
Relative Frequency Tables
Grouped Frequency Tables
Percentile and Percentile Rank Tables
4. Graphs and Plots
Why Use Graphs?
Graphing Continuous Data
Symmetry, Skew, and Kurtosis
Graphing Discrete Data
Part III. Central Tendency: Bull's-Eye
5. Mode, Median, and Mean
What Is Central Tendency?
Mode
Median
Mean
Skew and Central Tendency
Part IV. Dispersion: From Here to Eternity
6. Range, Variance, and Standard Deviation
What Is Dispersion?
Range
Variance
Standard Deviation
Average Absolute Deviation
Controversy: N Versus n - 1
Part V. The Normal Curve and Standard Scores: What's the Score?
7. Percent Area and the Normal Curve
What Is a Normal Curve?
History of the Normal Curve
Uses of the Normal Curve
Looking Ahead
8. z Scores
What Is a Standard Score?
Benefits of Standard Scores
Calculating z Scores
Comparing Scores Across Different Tests
9. Score Transformations and Their Effects
Why Transform Scores?
Effects on Central Tendency
Effects on Dispersion
A Graphic Look at Transformations
Summary of Transformation Effects
Some Common Transformed Scores
Looking Ahead
Part VI. Probability: Odds Are
10. Probability Definitions and Theorems
Why Study Probability?
Probability as a Proportion
Equally Likely Model
Mutually Exclusive Outcomes
Addition Theorem
Independent Outcomes
Multiplication Theorem
A Brief Review
Probability and Inference
11. The Binomial Distribution
What Are Dichotomous Events?
Finding Probabilities by Listing and Counting
Finding Probabilites by the Binomial Formula
Finding Probabilities by the Binomial Table
Probability and Experimentation
Looking Ahead
Nonnormal Data
Part VII. Inferential Theory: Of Truth and Relativity
12. Sampling, Variables, and Hypotheses
From Description to Inference
Sampling
Variables
Hypotheses
13. Errors and Significance
Random Sampling Revisited
Sampling Error
Significant Difference
The Decision Table
Type 1 Error
Type 2 Error
14. The z Score as a Hypothesis Test
Inferential Logic and the z Score
Constructing a Hypothesis Test for a z Score
Looking Ahead
Part VIII. The One-Sample Test: Are They From Our Part of Town?
15. Standard Error of the Mean
Central Limit Theorem
Sampling Distribution of the Mean
Calculating the Standard Error of the Mean
Sample Size and the Standard Error of the Mean
Looking Ahead
16. Normal Deviate Z Test
Prototype Logic and the Z Test
Calculating a Normal Deviate Z Test
Examples of Normal Deviate Z Tests
Decision Making With a Normal Deviate Z Test
Looking Ahead
17. One-Sample t-Test
Z Test Versus t Test
Comparison of Z-Test Versus t-Test Formulas
Degrees of Freedom