# MAT 120 Probability & Statistics Mathematics

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1 MAT 120 Probability & Statistics Mathematics Catalog Course Description: This course includes the following topics: introductory probability and statistics, including organization of data, sample space concepts, random variables, counting problems, binomial and normal distributions, central limit theorem, confidence intervals, and hypothesis testing for large and small samples; Types I and II errors; linear regression; and correlation. Prerequisite(s): MAT 102 Credit Hours: 3.0 Credit Hours D2L Brightspace Login Page: Departmental Assistant: Department Chair: Program Coordinator: Ms. Mitzi Trigg Mr. Rick Bailey Ms. Rose Jenkins Textbook(s): Elementary Statistics, 12 th Edition, by Mario Triola; Pearson Education, Inc., 2014 Additional Course Equipment: 1. Graphing calculator, TI-84 or TI-84+ Course Objectives: Upon completion of this course the student will be able to: 1. Understand the role statistics plays in supporting decision making. 2. Understand the strengths and weaknesses of statistical inference. 3. Collect data and make accurate analysis of all the collected data. 4. Solve problems by identifying what information is available and relevant to the problem. 5. Solve problems by selecting or developing appropriate procedures and relationships. 6. Solve problems by correctly applying the methods selected to the information available. 7. Solve problems by verifying the validity and appropriateness of the solution. Program and course assessment activities are deployed and results collected in accordance with the College s assessment schedule. Please refer to the information in the syllabus regarding the applicability of the assessment activity for the current semester. Course Outcomes and Competencies: Intended Course Outcome 1: Students should meet the general education core competency in mathematics. Course Competency 1: Students should be able to evaluate and solve systematically problems requiring computational skills, quantitative reasoning and symbolic reasoning. Intended Course Outcome 4: Students should be able to solve mathematical application problems appropriate to the course in all college transfer level mathematics courses. Course Competency 4: Students should be able to solve problems at the college transfer level by identifying what information is available and relevant to the problem; by selecting or developing

2 appropriate procedures and relationships; by correctly applying the methods selected to the information available; and by verifying the validity and appropriateness of the solution. Performance Measurement Instrument: Students will be given four applied mathematical problems to solve selected by the Mathematics Department to measure successful attainment of the competency. These problems will be embedded within student chapter tests and the final exam. A student scoring at least 3 out of 4 will be considered to have successfully attained the competency. The goal is for 80% of the students completing the assessment to successfully attain the competency. Course Attendance On Campus Course Attendance: ABSENCE - Failure to be present for a scheduled meeting of the class or arriving for the class more than ten minutes after the scheduled time for the class to begin. TARDY --- Arrival to class after the instructor has called the roll and before ten minutes past the time scheduled for the class to begin. I. Absences are counted from the first day of classes. II. Two absences are allowed for a class that meets once per week, three absences are allowed for a class that meets two times per week and five absences are allowed for a class that meets three times per week. III. Three tardies are considered as one absence. The student must meet with the instructor at the end of the class to which he has been late to have the absence changed to a tardy. IV. There are no "excused" absences; all absences are counted, regardless of the reason for the absence. V. A student missing class time by leaving early will also be counted absent. Online Course Attendance: Online instructors will establish and communicate to students the guidelines for determining attendance in their online courses. Attendance should be established along the same guidelines as on campus courses (see above). Attendance can be counted in a variety of ways such as identifying how many missing assignments constitute an absence or identifying a certain percentage of assignments that must be turned in for the student to be in attendance the required amount of time. Instructors should withdraw any students who exceed the total number of allowed absences. Hybrid Course Attendance: Hybrid instructors will count both on ground and online absences (as defined in the course syllabus and policies) in determining total absences in a hybrid course (see above). Instructor should establish and communicate to students what constitutes in class attendance and what constitutes online attendance. Instructor must be specific in what the online activities are and how they are graded. Students should be counted absent when they fail to participate in or submit specified online activities and/or assignments that equate to a class meeting. Tardies apply for on campus portion of course. Instructors should withdraw any students who exceed the total number of allowed absences, whether in class, online, or in combination. Please note the following: You are responsible for all material and announcements presented, whether you are present or absent.

5 Current Week Topics Covered Section Discrete Probability Distributions Review and Preview 5-1 Probability Distributions 5-2 Binomial Probability Distributions 5-3 Week 8 Parameters for Binomial Distribution 5-4 Normal Probability Distributions Review and Preview 6-1 The Standard Normal Distribution 6-2 Applications of Normal Distributions 6-3 Week 9 Sampling Distributions and Estimators 6-4 The Central Limit Theorem 6-5 Normal as Approximation to Binomial (optional) 6-7 Week 10 TEST 3 Estimates and Sample Sizes Review and Preview 7-1 Estimating a Population Proportion 7-2 Week 11 Estimating a Population Mean 7-3 Hypothesis Testing Review and Preview 8-1 Basics of Hypothesis Testing 8-2 Week 12 Testing a Claim about a Proportion 8-3 Testing a Claim about a Mean 8-4 TEST 4 Week 13 Correlation and Regression Review and Preview 10-1 Correlation 10-2 Regression 10-3 Week 14 Prediction Intervals and Variation 10-4 TEST 5 Final Exam or Final Project

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