Elementary Statistics Using the TI-83/84 Plus Calculator

Mario F. Triola is a Professor Emeritus of Mathematics at Dutchess Community College, where he has taught statistics for over 30 years. Marty is the author of Elementary Statistics, 10th Edition, Elementary Statistics Using Excel, Elementary Statistics Using the TI-83 84 Plus Calculator, and he is a co-author of Biostatistics for the Biological and Health Sciences, Statistical Reasoning for Everyday Life and Business Statistics. He has written several manuals and workbooks for technology supporting statistics education. Outside of the classroom, Marty has been a speaker at many conferences and colleges. His consulting work includes the design of casino slot machines and fishing rods, and he has worked with attorneys in determining probabilities in paternity lawsuits, identifying salary inequities based on gender, analyzing disputed election results, analyzing medical data, and analyzing medical school surveys. Marty has testified as an expert witness in New York State Supreme Court. The Text and Academic Authors Association has awarded Mario F. Triola a “Texty” for Excellence for his work on Elementary Statistics.

1. Introduction to Statistics

Overview

Types of Data

Critical Thinking

Design of Experiments

Introduction to the TI-83/84 Plus Calculator


2. Summarizing and Graphing Data

Overview

Frequency Distributions

Histograms

Statistical Graphics

 

3. Statistics for Describing, Exploring, and Comparing Data

Overview

Measures of Center

Measures of Variation

Measures of Relative Standing

Exploratory Data Analysis (EDA)


4. Probability

Overview

Fundamentals

Addition Rule

Multiplication Rule: Basics

Multiplication Rule: Complements and Conditional Probability

Probabilities Through Simulations

Counting

Bayes’ Theorem (on CD-ROM)


5. Probability Distributions

Overview

Random Variables

Binomial Probability Distributions

Mean, Variance, and Standard Deviation for the Binomial Distribution

The Poisson Distribution


6. Normal Probability Distributions

Overview

The Standard Normal Distribution

Applications of Normal Distributions

Sampling Distributions and Estimators

The Central Limit Theorem

Normal as Approximation to Binomial

Assessing Normality


7. Estimates and Sample Sizes

Overview

Estimating a Population Proportion

Estimating a Population Mean: s Known

Estimating a Population Mean: s Not Known

Estimating a Population Variance


8. Hypothesis Testing

Overview

Basics of Hypothesis Testing

Testing a Claim About a Proportion

Testing a Claim About a Mean: s Known

Testing a Claim About a Mean: s Not Known

Testing a Claim About Variation


9. Inferences from Two Samples

Overview

Inferences About Two Proportions

Inferences About Two Means: Independent Samples

Inferences from Matched Pairs

Comparing Variation in Two Samples


10. Correlation and Regression

Overview

Correlation

Regression

Variation and Prediction Intervals

Multiple Regression

Modeling


11. Multinomial Experiments and Contingency Tables

Overview

Multinomial Experiments: Goodness-of-Fit

Contingency Tables: Independence and Homogeneity

McNemar’s Test for Matched Pairs


12. Analysis of Variance

Overview

One-Way ANOVA

Two-Way ANOVA


13. Nonparametric Statistics

Overview

Sign Test

Wilcoxon Signed-Ranks Test for Matched Pairs

Wilcoxon Rank-Sum Test for Two Independent Samples

Kruskal-Wallis Test

Rank Correlation

Runs Test for Randomness


14. Statistical Process Control

Overview

Control Charts for Variation and Mean

Control Charts for Attributes


15. Projects, Procedures, Perspectives

Projects

Procedures

Perspectives


Appendices

Appendix A: Tables

Appendix B: Data Sets

Appendix C: Glossary

Appendix D: Bibliography

Appendix E: Answers to Odd-Numbered Exercises (and all Review Exercises and all Cumulative Review Exercises)


Credits
Index