# MTH210 Probability and Statistics

Lead Faculty: Dr Igor Ya Subbotin

## Course Description

An introduction to statistics and probability theory. Covers simple probability distributions, conditional probability (Bayes Rule), independence, expected value, binomial distributions, the Central Limit Theorem, hypothesis testing. Assignments may utilize the MiniTab software, or text-accompanying course-ware. Computers are available at the University's computer lab. Calculator with statistical functions is required.

## Learning Outcomes

- Use statistical vocabulary.
- Construct various frequency distributions of grouped and ungrouped data.
- Calculate and interpret descriptive statistics of samples and populations. (Measures of central tendency, measures of dispersion.)
- Calculate simple probabilities.
- Find the mean and variance of a probability distribution including the binomial distribution.
- Understand and calculate expected values.
- Calculate the probabilities or scores of normal distributions and the normal approximation of the binomial distribution.
- Use the Central Limit Theorem to calculate the probabilities of the mean for any distribution.
- Formulate, calculate and interpret hypotheses test for one parameter and to compare two parameters, for both large and Small samples, Z and T for one two samples.