STAT 206

#class

Statistics for Software Engineering

Prereqs: Math 115, Math 119

It [the midterm] was fairly straighforward (it was not)
- Steve Van Doormaal

If you look at this [T] table, its shape is suspiciously similar to the Z-score table
- SVD

1. 1. Intro to Probability
   2. "Counting Rules"
      • Addition rule
        • Addition Rule (OR Rule): If an experiment can be one in or different ways, the total number of possibilities is
      • Multiplication Rule
        • Multiplication Rule (AND Rule): If an experiment can be done in ways and experiment can be done in ways, then the number of total possibilities is
      • Permutations and Combinations
      • Axioms of Probability
      • The Inclusions-Exclusion Principle (Don't "double count")
   3. Conditional probability
      • Conditional Probability
      • Statistical Independence
      • Mutually Exclusive Events
   4. Law of Total Probability and Baye's Theorem
2. 1. Probability Distributions
      • Expectation
      • Variance
   2. Discrete Probability Distributions
      • Bernoulli Distribution
      • Binomial Distribution
      • Geometric Distribution
      • Negative Binomial Distribution
      • Hypergeometric Distribution
      • Poisson Distribution
   3. Continuous Probability Distributions
      • Uniform Continuous Distribution
      • Exponential Distribution
      • Normal Distribution
        • Standard Scores
        • The Sampling Distribution of the Sample Mean
        • Central Limit Theorem
3. 1. Data Analysis and Statistical Inference
      • Sampling Methods
      • Interquartile Range
   2. Statistical Modeling
      • Confidence Intervals