Many students find the material in this course to be interesting, and often fun, but take note: virtually all questions are “word problems” and answers are highly dependent on how questions are worded. You will need to read each question carefully to determine what it is asking, then decide which of several techniques is appropriate to obtain a correct solution. Strong analytical and critical-thinking skills are a must to succeed.
The textbook for this course is McGraw-Hill Ryerson’s Mathematics of Data Management 12.
Probability Project Samples
Topics Covered
- Statistical Measures
- Statistical Analysis
- Sampling Techniques
- Bias
- Correlation
- Linear Regression
- Non-Linear Regression
- Cause and Effect
- Critical Analysis
- Counting and Permutations
- Sets and Combinations
- Lesson: Sets
- Lesson: Principle of Inclusion and Exclusion
- Combinations
- Combinations with Repetition
- Problem Solving with Combinations
- Other Counting Techniques
- Pascal’s Method and Binomial Theorem
- Patterns In Pascal’s Triangle
- Pascal’s Triangle and Combinations
- Pascal’s Method
- Binomial Theorem
- Probability
- Probability Distributions
- Normal Probability Distribution
- Lesson: Properties of the Normal Distribution
- Worksheet: Properties of the Normal Distribution
- Lesson: Probabilities Using the Normal Distribution
- Worksheet: Probabilities Using the Normal Distribution
- Handout: Z-Table for the Normal Distribution
- Lesson: The Normal Distribution and Discrete Data
- Lesson: Normal Approximation to the Binomnial Distribution