Learning Statistics

Introduction

We wanted to create a introduction to statistics that was approachable to any individual in any field.  We tried to provide in depth explanations for the concepts presented.  We also tried to provide engaging questions to test your knowledge and understanding.  We include how to solve the same problems using R because we believe that R is very important.  We believe that R is a tool that every person should know.  While knowing how to use a calculator is important, it has become equally, if not more, important to know how to do computational statistics.  While doing R for introductory statistics is not as complex as other topics, it will provide a helpful beginning step for those that have never coded or done statistics before.

If you have already master introductory statistics but you would like to learn how to use R, click here instead.

Content

• Learning Introductory Statistics
  • What is Statistics
  • Terminology and Opening Concepts
    • Data Types
  • Measures of Central Tendency
    • Mean, median, mode
    • Skewed Distributions
  • Measures of Variability
    • Range, Variance, and Standard Deviation
  • Normal Distribution
    • What is the normal distribution?
    • Probability and the normal distribution
    • QQ Plot
  • Standardization and z Scores
    • Standardizing data
    • Z-scores
    • p-Values
  • Critical Values and Hypothesis Testing
    • Critical Values
    • One-Tailed Testing
    • Two-Tailed Testing
  • Confidence Intervals
  • t Distribution
    • The t-distribution
    • t Scores and z Scores
    • Independent Samples t Tests
    • Paired or Dependent  t Tests
  • Correlation
    • Pearson Correlation Coefficient
    • Other correlation coefficients
  • The Chi-Square Statistics
    • Chi Square Test