MATH 217 - Statistics for Scientists

A course in statistical methods for students in STEM disciplines. The course will explore foundational concepts and applications in descriptive and inferential statistics including: conditional probability, sampling distribution, estimation, odds ratios, formal probability distributions (e.g., binomial, Gaussian and Poisson), confidence intervals, hypothesis testing (e.g., t-tests, Wilcoxon Rank Test, ANOVA, chi-square tests), correlation, simple and multiple linear regression, relative risk, and logistic regression. Coursework will rely heavily on technology in order to focus on the applications of statistical concepts and methods within STEM disciplines. PRE- or COREQUISITE(S): MATH 150 or MATH 170 or MATH 181 or consent of department. Three hours each week.

3 semester hours

Course Outcomes:
Upon completion of this course, a student will be able to:

Describe the role of descriptive and inferential statistics within the framework of scientific method.
Examine various probability distributions and their relevant applications.
Describe, apply, and communicate the theories and practices of parametric and non-parametric statistical computations including summary measures, statistical inference, probability, hypothesis testing, confidence intervals, simulations, regression analysis and modeling, and odds ratios.
Utilize technology to explore, transform, visualize, and perform statistical computations to analyze multifaceted authentic datasets and communicate insights using a responsible workflow.
Evaluate and apply ethical principles and practices in statistics.

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