Offers study of some area of computer science in more depth than is possible in the usual classroom setting. Students work on projects under the direction of faculty members. Prerequisite: Department approval. (P/F)
MATH 155 MOD STATISTICS WITH COMPUT (Fall 2019)
Descriptive and inferential analysis of raw data, emphasizing appropriate assumptions, computer use and interpretation. Consideration of parametric and nonparametric methods and comparison of their powers. Intended for students in the social and natural sciences. May not receive credit for more than one: MATH 150, 155, 213 or 216. Prerequisites: High school Algebra II and plane geometry. Three hours per week. Meets General education IVB or IVC.
MATH 216 STATISTICAL THINKING (Fall 2019)
Descriptive and inferential analysis of data, emphasizing appropriate assumptions, computer use and interpretation. Parametric and non-parametric methods are compared and contrasted. Includes a weekly laboratory. May not receive credit for more than one: MATH 150, 155, 213 or 216. Prerequisite or Corequisite: C or better or concurrent enrollment in MATH 160, 198, 201 or similar calculus experience. Four hours per week.
MATH 314 REGRESSION ANALYSIS (Fall 2019)
The study of relationships among variables. Correlation, simple linear regression and multiple regression analyses are studied. Other topics such as Ridge regression and logistic regression also are considered. Computer software such as Minitab and SPSS is used. Prerequisite: C or better in MATH 151 or 155 or 213 or 216. Four hours per week. Meets General Education IVB or IVC.