Buy New MATH 211 Introduction to Statistical Analysis
Course Description
An introduction to statistical analysis for students with a background in calculus. Included in the topics covered are probability distributions, expectation, statistical inference, regression and correlation.
For information regarding the prerequisites for this course, please refer to the Academic Course Catalog.
Rationale
As members of a society increasingly devoted to the use and misuse of numbers, students must learn to correctly interpret statistical presentations in all areas and especially in their major fields. This course is designed to give the students a working knowledge of statistics with an emphasis on application rather than theory.
Measurable Learning Outcomes
Upon successful completion of this course, the student will be able to:
- MLO 1: Compute probabilities associated with multiple events.
- MLO 2: Compute the mean and variance of several common discrete and continuous probability distributions and use them in practical applications.
- MLO 3: Create confidence intervals for unknown parameters.
- MLO 4: Perform hypothesis tests.
- MLO 5: Determine the correlation between two variables and develop linear regression models which predict the value of one variable as a function of the other.
General Education Foundational Skill Learning Outcomes: Technological Solutions and Quantitative Reasoning (TSQR)
- TSQR 1: Analyze data and inform action through a structured method.
- TSQR 2: Predict the output based on input in practical scenarios using technological solutions and/or quantitative reasoning.
- TSQR 4: Relate technology and quantitative reasoning to participation in God’s redemptive work.
Course Assignment
Textbook readings and lecture presentations/notes
Course Requirements Checklist
After reading the Course Syllabus and Student Expectations, the student will complete the related checklist found in the Course Overview.
Discussion: Lies and Statistics?
The discussion introduces some of the ethical challenges that are specific to the practice of statistics and encourages students to approach these situations from a Christian perspective (FSLOs: TSQR 4).
Homework Assignments (8)
The student will complete a homework assignment each module/week in the WebAssign that is associated with the course textbook. Typically, assignments will cover 4 – 5 sections from the textbook, but this will vary depending on the length and difficulty of each section included in the assignment. Students will be required to earn a 70% on each assignment before moving on to the next homework assignment or test (MLOs: MLO 1, 2, 3, 4, 5; FSLOs: TSQR 1, 2).
Project: Password Security Assignment
This project applies combinatorics to an important real-life application and further explores topics introduced in the text. (MLOs: MLO 1, 3; FSLOs: TSQR 1, 2).
Project: Introduction to Cryptography Assignment
This project uses confidence intervals to analyze letter frequencies and applies this to decrypting a fairly simple type of coded message. It’s an application of inferential statistics within the area of cyber-security, broadly defined. (MLOs: MLO 1, 3; FSLOs: TSQR 1, 2).
Quiz: Exams (4)
Each test will cover the Learn material for two modules: the material assigned during the test module/week and the material from the previous module/week. Tests are not cumulative. Each test will be open-book/open-notes, contain 12-14 multiple-choice and short-answer questions, and have a 3-hour time limit. These tests will be completed in the WebAssign that is associated with the course textbook (MLOs: MLO 1, 2, 3, 4, 5; FSLOs: TSQR 1, 2).
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