MindEdge's Introductory Statistics learning resource shows students topics in statistics. Students explore the fundamentals of statistics while simultaneously applying this knowledge to real-world scenarios involving graphs, charts, tables of data, and word problems. Students solve various problems through the lens of a statistician, using a variety of tools to develop solutions.

This modular course can be tailored to your school with webtexts, ebooks, and optional trade paperbacks available. It seamlessly integrates into all learning management systems.

The course includes pretests and self-assessments, interactive exercises, graphics, and games that appeal to a variety of learning styles. Open ended questions that apply topics to real world problems give students opportunities to apply critical thinking skills to real-world statistics scenarios.

Topics covered in this course include:

  • Data, sampling, and data collection
  • Experimental design
  • Frequency, frequency tables, and levels of measurement
  • Measures of central tendency
  • Graphical representation of descriptive statistics
  • Independent and mutually exclusive events
  • Representing probability visually
  • Variance and standard deviation
  • Probability distribution function for a discrete random variable
  • Continuous probability functions
  • Exponential distribution
  • The standard normal distribution
  • Applications of the normal distribution
  • The central limit theorem
  • Student t-distribution
  • Hypothesis tests on two population means
  • Test of a single variance
  • Linear equations
  • Regression
  • The F distribution

The 13 modules of this course are as follows:

  1. Sampling and Data
  2. Descriptive Statistics
  3. Probability Topics
  4. Discrete Random Variables
  5. Continuous Random Variables
  6. The Normal Distribution
  7. The Central Limit Theorem
  8. Confidence Intervals
  9. Hypothesis Testing with One Sample
  10. Hypothesis Testing with Two Samples
  11. The Chi-Square Distribution
  12. Linear Regressions and Correlation
  13. F Distribution and One-Way ANOVA