What is the purpose of studying and understanding statistics, both descriptive and inferential?

What is the purpose of studying and understanding statistics, both descriptive and inferential?

The focus of this course is on understanding and properly using the concepts and language of descriptive and inferential statistics in the context of research. During this course, you will develop important critical thinking skills as you interpret and critique data analyses in various research designs. Mastery in these areas will improve your ability to effectively communicate and report statistical reasoning and results using professional language and APA formatting.

The first week of the course provides a foundation of the study of statistics in the behavioral sciences. We will explore the basic concepts, characteristics, and types of statistics, variables, and distributions. In addition, you will explore the different ways of describing data using measures of central tendency, variability, and the normal distribution.

You should consider the following questions before and during the readings and assignments this week:

1. What is the purpose of studying and understanding statistics, both descriptive and inferential?
2. What are the differences between the following concepts: descriptive and inferential statistics; populations and samples; parameters and statistics; independent and dependent variables; and scales of measurement (i.e., nominal, ordinal, interval, and ratio)?
3. How are frequency distributions used to organize and graphically represent data? What can the shape of the frequency distribution tell us about the data?
4. What are the different measures of central tendency and variability? How are they calculated or determined?
5. What are the characteristics of a normal distribution?
6. When and why would we use z scores and means?

Learning Outcomes

Upon successful completion of this week, students will be able to:

1. Explain the difference between a sample and the population. (Aligns with CLOs 1)
2. Identify the various attributes of a variable (e.g., discrete versus continuous, quantitative versus categorical, and scale of measurement). (Aligns with CLOs 1)
3. Explain the characteristics and usefulness of a normal distribution. (Aligns with CLOs 1)
4. Interpret z scores. (Aligns with CLOs 1)

Overview

AssignmentDueFormatValueCLOsIntroduction DiscussionDay 1 (1st post)Discussion Forum1N/AResearch Question BrainstormDay 3 (1st post)Discussion Forum3N/ASmart Lab LessonsDay 7Written Assignment5N/A10 Unique Research QuestionsDay 7Written Assignment5N/ATotal14

Resources

Required Text

Sukal, M. (2013). Research methods: Applying statistics in research. San Diego, CA: Bridgepoint Education, Inc.
Chapter 1: Quantitative Problem Solving
Chapter 2: Illustrating Data
Chapter 3: The Standard Normal Distribution and z Scores

Carruthers, M. W., Maggard, M. (2012). SmartLab: A Statistics Primer. San Diego, CA: Bridgepoint Education, Inc.
Lesson 1: Populations and Samples
Lesson 2: Variables and Measurement
Lesson 4: Measures of Central Tendency (Mean, Median, and Mode)
Lesson 5: Measures of Variability

SMARTLab Tests: The SMARTLab is a self-paced, online basic statistics course designed to prepare you for your graduate courses and graduate research.
Lesson 1: Sampling
Lesson 2: Variables
Lesson 4: Central Tendency
Lesson 5: Variability