Listed in: Mathematics and Statistics, as STAT-370 | Mathematics and Statistics, as MATH-370
Formerly listed as: MATH-30
Nicholas J. Horton (Section 01)
(Offered as STAT 370 and MATH 370) This course examines the theory underlying common statistical procedures including visualization, exploratory analysis, estimation, hypothesis testing, modeling, and Bayesian inference. Topics include maximum likelihood estimators, sufficient statistics, confidence intervals, hypothesis testing and test selection, non-parametric procedures, and linear models.
Requisite: STAT 111 or STAT 135 and STAT 360, or consent of the instructor. Limited to 25 students. Spring semester. Professor Horton.
If Overenrolled: Priority to STAT majors
Section 01
W 02:00 PM - 03:50 PM WEBS 102
F 02:00 PM - 03:50 PM WEBS 102
This is preliminary information about books for this course. Please contact your instructor or the Academic Coordinator for the department, before attempting to purchase these books.
| ISBN | Title | Publisher | Author(s) | Comment | Book Store | Price |
|---|---|---|---|---|---|---|
| Mathematical Statistics and Data Analysis | Cengage | Rice | 3rd edition (CD not required) | Amherst Books | TBD | |
| Using R and RStudio for Data Management, Statistical Analysis, and Graphics | CRC Press | Horton and Kleinman | Optional | Amherst Books | TBD |
These books are available locally at Amherst Books.