MAT 2600 Applied Statistics
Covers sample spaces and probability laws; discrete and continuous random variables with special emphasis on the binomial, Poisson, hypergeometric, normal and gamma distributions; fundamental sampling distributions and data descriptions; use of computer software packages for simulating, summarizing, and displaying data. Provides a foundation for the further study of statistics.
Division: Science, Technology, Engineering and Mathematics
Department: Mathematics
Repeatable Credit: No
Offered Online: No
Prereqs: MAT 2280
Outcomes
- Distinguish various types of discrete probability distributions such as binomial, negative binomial, multinomial, hypergeometric, and Poisson distributions. Calculate the probabilities according to different probability models.
- Identify discrete and continuous random variables. Use integrals to calculate probabilities for continuous random variables. Construct and evaluate joint probability and marginal distributions. Calculate the mean, variance, and covariance of random variables.
- Distinguish various types of continuous probability distributions such as normal, gamma, exponential, and chi-square distributions. Use the normal distribution to approximate the binomial distribution. Calculate the probabilities according to different probability models.
- Use the Central Limit Theorem to evaluate sampling distribution of means. Use chi-square for sampling distribution of variance. Identify the usage for t and F distributions.
- Evaluate basic probabilities including conditional probability with appropriate rules.
Credit Hours: 3
Classroom Hours: 3