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# MATH 2025 - Probability and Statistics with Calculus

Credits: 4
Hours/Week: Lecture 4Lab None
Course Description: This calculus-based course is intended for students majoring in statistics, mathematics, computer science, and some engineering programs. Topics include descriptive statistics, probability, probability distributions for discrete and continuous random variables, joint probability distributions, point estimation, and inferences based on one and two samples. Analysis and interpretation of data using a software package and/or the TI-83/84 series calculator, is required.
MnTC Goals
None

Prerequisite(s): MATH 1082  with a grade of C or higher.
Corequisite(s): None
Recommendation: Assessment score placement in RDNG 1000  or above, or completion of RDNG 0900  or RDNG 0950  with a grade of C or higher.

Major Content
1. Confidence intervals
2. Descriptive statistics
1. Visual representations
2. Numerical measures
3. Hypothesis testing
4. Joint probability distributions
5. Point estimation
6. Probability distributions
1. Discrete random variables
2. Continuous random variables
7. Probability

Learning Outcomes
At the end of this course students will be able to:

1. distinguish between different types of point estimations. (i.e. unbiased, method of moments, and maximum likelihood)
2. display data sets through numerical summary measurements and visual representations.
3. construct and interpret confidence intervals.
4. compute probabilities through the use of calculus and density functions for continuous random variables.
5. compute probabilities through the use of joint density functions for two random variables.
6. compute probabilities through the use of density functions and the cumulative distribution functions for discrete random variables.
7. determine probabilities of certain events and interpret the results.
8. design hypothesis tests for various parameters and calculate p-values.