Introduction to Probability and Statistics – BUSI 230

CG • Section 8WK • 11/08/2019 to 04/16/2020 • Modified 07/28/2020

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 MATH 201)

Prerequisites

Placement Score-Math with a score of 75 or (CLST 103 and Assessment - Mathematics II with a score of 15 and Assessment - Mathematics with a score of 23) or MATH 108 or MATH 110 or MATH 115 or MATH 121 or MATH 126 or MATH 128 or MATH 131 or MATH 1XX or MATH 2XX

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:

1. Construct and interpret appropriate graphical representations of data.
2. Compute statistical measures which describe the location, dispersion, and placement of data values.
3. Compute probabilities associated with multiple events and common distributions.
4. Create confidence intervals for unknown parameters.
5. Perform hypothesis tests.
6. 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)

1. TSQR 1: Analyze data and inform action through a structured method.
2. TSQR 2: Predict the output based on an input in practical scenarios using technological solutions and/or quantitative reasoning.
3. TSQR 4: Relate technology and quantitative reasoning to participation in God’s redemptive work.

Course Assignment

Course Requirements Checklist

After reading the Course Syllabus and Student Expectations, the student will complete the related checklist found in Module/Week 1.

Course Introduction Quiz

The student must complete the Course Introduction Quiz in WebAssign and must receive a score of 100% before he/she can start any of the other assignments in WebAssign. This quiz will be open-book/open-notes and cover information from the Course Syllabus and announcements offered in Module/Week 1. The student will receive unlimited attempts for this quiz.

Exercises (8)

Each module/week, the student will complete a set of exercises which will correlate with the assigned Reading & Study material. These exercises will be completed using WebAssign (MLO: A, B, C, D, E, F; TSQR 1, 2).

Projects (4)

Modules/Weeks 1, 3, 5, and 7 will each have an individual project. These projects will apply statistics to real-life situations and demonstrate links between statistics and the Bible. Projects 2 and 4 will be completed in Discussion Board Forums 1 and 2 (MLO: A, B, E; TSQR 1, 2, 4).

Core Competency Quiz

This quiz covers material from the course selected to align with Liberty University’s Core Competency Learning program. The quiz is open-book/open-notes and will be assigned in WebAssign (MLO: A; TSQR 1).

Exam Reviews (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 WebAssign (MLO: A, B, C, D, E, F; TSQR 1, 2).

Exams (4)

The student will complete exams during Modules/Weeks 2, 4, 6, and 8. Each exam will be have a time limit of 3 hours, will be open-book/open-notes, and will cover 2 modules/weeks of material. The exams will be taken in WebAssign (MLO: A, B, C, D, E, F; TSQR 1, 2).