Mathematics (MATH) 315

Methods in Applied Statistics (Revision 1)

MATH 315 Course cover

Revision 1 is temporary closed, effective September 29, 2020

Delivery Mode: Individualized study online*

Credits: 3

Area of Study: Science

Prerequisite: MATH 215 or MATH 216 or MGSC 301 or SOCI 301 or any equivalent introductory quantitative statistical methods course

Precluded Course: MGSC 312 (MATH 315 may not be taken for credit if credit has already been obtained for MGSC 312.)

Faculty: Faculty of Science & Technology

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*Note: This course requires the use of the statistical package IBM® SPSS® Statistics Standard GradPack 22 (or higher). Students must lease this proprietary software independently from a reliable source.


Mathematics 315: Methods in Applied Statistics is designed to enable students to develop familiarity with various parametric and nonparametric tests and to gain the knowledge and skills needed to apply statistical concepts to solve applied problems. Students will learn the logic, the procedures and the use of common statistical techniques using one of the most commonly used statistical packages - SPSS for Windows.

Course Objectives

After completing this course, a student will have

  • an in-depth knowledge of basic statistical principles;
  • a basic understanding of experimental design;
  • facility with a wide range of statistical tests, including correlation, simple and multiple linear regression models, single and two factor analysis of variance and logistic regression; and
  • proficiency in the analysis of a wide range of data sets selected from the biological, physical and social sciences, and from business applications.


Mathematics 315 consists of the seven units listed below:

  • Unit 1: Introduction to Research Design Concepts
  • Unit 2: Nonparametric Tests
  • Unit 3: Analysis of Variance (AOV) and Multiple Comparison Procedures
  • Unit 4: Simple Linear Regression and Correlation
  • Unit 5: Multiple Linear Regression and the General Linear Model
  • Unit 6: More on One-way AOV (Completely Randomized Designs)
  • Unit 7: Analysis of Variance for Blocked Designs


To receive credit for MATH 315, you must achieve a mark of at least 50 per cent on each of the following: the midterm examination, the final examination and achieve a composite course grade of D (50 percent). The weighting of the composite grade is as follows:

Activity Weighting
TME 1 5%
TME 2 5%
TME 3 5%
Midterm Exam 30%
TME 4 5%
TME 5 5%
TME 6 5%
Final Exam 40%
Total 100%

To learn more about assignments and examinations, please refer to Athabasca University's online Calendar.

Course Materials


Methods in applied statistics: Custom text for Math 315, Athabasca University (2012). Toronto: Nelson Education.

Methods in applied statistics: Custom solutions manual for Math 315, Athabasca University (2012). Toronto: Nelson Education.

Other Materials

The course materials also include an online study guide, course manual and SPSS instructional manual.

Special Course Features

You will need to purchase or lease a license for IBM® SPSS® Statistics Standard GradPack 22 (or higher) to complete this course. The IBM® SPSS® Statistics Standard GradPack (omit 22) includes: Statistics Base, Advanced Statistics, and Regression. Sources for this software include, but are not limited to the AU Bookstore, OnTheHub eStore, Student, and

Be aware that any non-programmable, non-graphing calculators may be taken into the exam rooms.

However, students are NOT allowed to bring a programmable or graphing calculator (with or without installed statistical applications), a cell phone, a digital camera, a PDA, an iPod or any similar electronic device into the examination rooms. Computers of any sort are NOT permitted except under specially approved circumstances (i.e., for some students with disabilities). Students are also NOT allowed to consult with any person when writing the examinations for this course.

Athabasca University reserves the right to amend course outlines occasionally and without notice. Courses offered by other delivery methods may vary from their individualized-study counterparts.

Opened in Revision 1, July 30, 2013.