MATH.2112.Averett.Syvillia.20102.201802 (1).docx

MATH.2112.Averett.Syvillia.20102.201802 (1).docx - MATH...

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MATH 2112, Probability and Statistics CRN: 20102 Spring 2018 Course Format: Online INSTRUCTOR INFORMATION Instructor: Syvillia Averett, Ph.D . Title: Assistant Professor of Mathematics Office: Correll 116J (Brunswick) Phone: (912) 279-4577 Office Hours: The hours below are face-to-face office hours. I will be available via Blackboard Collaborate at these times as well if you would like to meet remotely. You may also schedule an appointment with me of these times do not cooperate with your schedule. Monday Tuesday Wednesday Thursday Friday 9:00-11:00 AM 2:00-4:00 PM 9:00-11:00 AM 2:00-4:00 PM By Appointment Only While this course is offered in an online format, you are not in it alone. Use all of your available resources so that you can have the most meaningful experience. A Study Lounge for students to discuss this course is provided on the course D2L page under Content>Module 0:Getting Started > Office Hours and Study Lounge> Study Lounge>Collaborate Ultra. It is an open session and may be accessed anytime outside of exam windows until final exam week. E-mail: [email protected] Expected Response Time : Students should expect a response to any correspondence within one business day. Responses may take longer over the weekend, but should not exceed 48 hours. Exceptions to this policy include breaks and holidays. Preferred Contact Method: I prefer to be contacted via the CCGA e-mail provided above. Please do not e- mail me using D2L email. COURSE DESCRIPTION Catalog Description: 3 class hours, 3 credits Prerequisite: MATH 1001 or MATH 1111 or MATH 1113 This course includes an introduction to statistics (data, vocabulary, uses and abuses of statistics, sampling, and statistical computing), descriptive statistics (graphical techniques and numerical techniques), probability distributions (discrete and continuous distributions), normal distribution (standard normal, nonstandard normal, z scores, and central limit theorem), estimation (point/interval), hypothesis testing (1 sample, 2 sample, ANOVA, correlational/regression), and MINITAB (or other statistical software) laboratory.
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Course Learning Outcomes: After successful completion of the course the student will be able to: 1. Interpret statistical information. 2. Perform elementary statistical procedures. 3. Apply basic statistical tools appropriately to describe data and make intelligent statistical decisions. 4. Use appropriate technology in the evaluation, analysis and synthesis of statistical information in problem- solving situations. General Education Outcomes: In addition to the course learning outcomes, this course will also address the College general education outcomes and competencies associated with Learning Goal Natural Sciences, Mathematics and Technology (Area D1) : Outcomes: Students will be able to demonstrate the ability to solve problems and draw conclusions by analyzing situations and explaining them in numeric, graphical or symbolic terms.
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