Communication Studies (CMNS) 308
Understanding Statistical Evidence (Revision 6)
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Delivery Mode: Individualized study online
Area of Study: Social Science
Prerequisite: None; however fundamental mathematical skills are required. The university offers an online test containing 70 questions that will help you assess your mathematical skills. If you are unsure about your ability to complete CMNS 308 / HSRV 308, you may wish to register in MATH 100 (a non-credit course) designed to assist students in strengthening their mathematical skills. You may also wish to contact the course coordinator for CMNS 308.
Precluded course: CMNS 308 may not be taken for credit if credit has already been obtained for HSRV 308.
CMNS 308 has a Challenge for Credit option.
Many people working in journalism, public relations and other communications fields need to be able to understand how statistics are used in order to present information and frame arguments. This course is designed for those who want to become critical consumers of statistical evidence. It emphasizes a conceptual rather than a computational approach to learning statistics. Using examples taken from popular media, the course explains how people use and abuse statistics for purposes of persuasion and influence.
There are eight units in the course.
Unit 1: Why Study Statistics?
The history of statistics, the importance of studying statistics, and the scope, structure and mechanics of the course.
Unit 2: The Significance of Sampling
Sampling procedures used to draw appropriate samples in order to make reliable and valid statements about populations; learn to evaluate the results of surveys and polls.
Unit 3: Understanding Scientific Experiments
Introduction to experimental designs and their implications for making causal statements; recognizing elements of bias in designs.
Unit 4: Measurement
A focus on the reliability and validity of the numbers generated in research; making informed judgements about reported conclusions based on numbers.
Unit 5: Describing Distributions
The ways numbers are organized and displayed, and the importance of measures of central tendency, dispersion or variability, and “normal” distributions; making accurate interpretations.
Unit 6: Understanding Relationships
Relationships between measures, or variables; understanding the results of multiple-variable research and the validity of related conclusions.
Unit 7: Probability: The Language of Chance
The language of probability, or the degree of likelihood of the occurrence of an event; the importance of probability for statistical tests of significance.
Unit 8: Inference: Conclusions with Confidence
Methods for drawing formal conclusions from data; making informed judgements about the use and abuse of inferential techniques. Unit 8 summarizes the course.
|Assignment 1 (after Unit 2)||6%|
|Assignment 2 (after Unit 4)||6%|
|Online Quiz 1 (after Unit 4)||4%|
|Essay (after Unit 4)||6%|
|Assignment 3 (after Unit 5)||6%|
|Assignment 4 (after Unit 6)||6%|
|Online Quiz 2 (after Unit 6)||4%|
|Assignment 5 (Unit 7)||6%|
|Assignment 6 (Unit 8)||6%|
|Online Quiz 3 (after Unit 8)||4%|
|Course End Project (after Unit 8)||14%|
To learn more about assignments and examinations, please refer to Athabasca University's online Calendar.
Crossen, Cynthia. (1994). Tainted truth: The manipulation of fact in America. New York: Simon and Schuster.
Moore, D. S., & Notz, W. I. (2017). Statistics: Concepts and controversies (9th ed.). New York: W. H. Freeman.
Challenge for Credit Overview
The Challenge for Credit process allows you to demonstrate that you have acquired a command of the general subject matter, knowledge, intellectual and/or other skills that would normally be found in a university-level course.
Full information about Challenge for Credit can be found in the Undergraduate Calendar.
|Part I: Take home essay exam||50%|
|Part II: Paper exam||50%|
Undergraduate Challenge for Credit Course Registration Form
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 6, April 25, 2019
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