Get Guided MATH 201 Introduction to Probability and Statistics 16 wk
Course Description
Introduction to descriptive statistics and probability, probability distributions, estimation, tests of hypotheses, chi-square tests, regression analysis, and correlation with applications in business and science. (Crosslisted with BUSI 230)
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 and construct statistical presentations in all areas of public discourse, especially in their major fields. This course emphasizes the major applications of statistical knowledge rather than its theory. The course seeks to educate men and women who will make important contributions to their workplaces and communities, follow their chosen vocations as callings to glorify God, and fulfill the Great Commission.
Measurable Learning Outcomes
Upon successful completion of this course, the student will be able to:
- Construct and interpret appropriate graphical representations of data.
- Compute statistical measures which describe the location, dispersion, and placement of data values.
- Compute probabilities associated with multiple events and common distributions.
- Create confidence intervals for unknown parameters.
- Perform hypothesis tests.
- 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
After reading the Course Syllabus and Student Expectations, the student will complete the related checklist found in the Course Overview.
In each module, the student will complete several sets of exercises that will correlate with the assigned Learn material. These exercises will be completed using Aleks. (MLO: A, B, C, D, E, F; TSQR 1, 2).
The culminating project is split into 5 assignments. This project will apply statistics to real-life data collection and analysis. (MLO: A, B, E; TSQR 1, 2, 4).
The review assignment for each exam must be completed with a grade of at least 70% before the exam can be taken. Each question on all the Exam Reviews can be worked as many times as needed to get full credit. All the Exam Reviews can be found in Aleks. (MLO: A, B, C, D, E, F; TSQR 1, 2).
Quizzes will be taken in Aleks and can be taken twice. Both attempts must be completed by the due date (MLO: A, B, C, D, E, F; TSQR 1, 2).
Each exam will be timed and open-book/open-notes. The exams will be taken in Aleks (MLO: A, B, C, D, E, F; TSQR 1, 2).
***You must submit all written work for the exam questions to the corresponding Written Work Submission Assignment in the module. Exams submitted without the accompanying work will not be accepted.
Written work for each exam must be submitted to the corresponding Written Work Submission Assignment page. Exams submitted without the accompanying work will not be accepted.
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