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Statistics: QR:Basic Statistical Methods 2

STAT 183 OL1 (CRN: 61793)

3 Credit Hours

About STAT 183 OL1

Quantitative statistical methodologies useful across disciplines. Analysis of variance, multiple and logistic regression, time series analysis, non-parametric methods, Bayesian statistics and decision analysis. Prerequisite: A grade of C or better in any of STAT 141, STAT 143, STAT 211, or EC 170.

Instructor

Related Program

Actuarial Exam Preparation Online Program

Notes

Dates: June 29 - August 7, 2020

More Information

Section Description

This course serves as a quantitative methods course for Business Administration Students. However, it is open to STATS/MATH majors and minors. There are 5 3-week modules covering: ANOVA, Regression, Time Series, Non-Parametric Testing, and Decision Analysis. There is an online homework component to review the pre-requisite material and practice the new material. There is a project required. A TI-83/84, JMP, and Excel is required for this course. Pre-requisites: STAT 141 or EC 170. We will be using an Edition (TBD) of Ken Black’s “Business Statistics For Making Contemporary Decisions”, Wiley.

Section Expectation

You will be expected to complete the homework (online and from the textbook), complete the case studies, discussion board and take all 5 exams. The usual for online courses (constant online presence) and keeping up with the work. You will need to purchase an access code for WileyPlus to complete this course.

Evaluation

Grading: Your grade for the course will be based on: • WileyPlus HW Quizzes (10%) • WileyPlus Tests (40%) • Case Studies / Projects (40%) • Discussion Board for Suggested Homework Problems from Textbook (10%) All assignments must be completed to receive a passing grade for the course.

Meetings

to

Location

Online (View Campus Map)

Important Dates

Note: These dates may change before registration begins.

Deadlines
Last Day to Add
Last Day to Drop
Last Day to Withdraw with 50% Refund
Last Day to Withdraw with 25% Refund
Last Day to Withdraw

Resources

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