# RESEARCH QUESTION BRAIN STORM (WK-1-DQ-1) (9-19-18)

March 27, 2021
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March 27, 2021

Research Question Brainstorm

Background

During this week you will brainstorm a list of research questions you are interested in, which will help you work towards your Week 1 Assignment. You are working towards creating a list of at least 10 unique research questions that encompass a variety of topics and types of variables. Think about exploring relationships between variables, making predictions for one variable using one or more other variables, and determining differences between groups across one or two variables. In future weeks, you will pull questions from this list that might lend themselves to a particular statistical analysis, thus saving valuable time in not needing to brainstorm research ideas. During those weeks you will take the research question and create a mini-research proposal that will help you consider the application of a specific statistical analysis to that question.

Discussion Assignment Requirements

Initial Posting – To earn full participation points, include in your initial posting at least 5 potential research questions by Day 3. Have fun with these questions and choose topics you are truly interested in, whether they are leadership, training, sports, social media, politics, movies, or food. This will make the research design process much more enjoyable. If you need help coming up with ideas, ask your instructor for examples. Also, feel free to post more than 5 research questions as it would be useful to get feedback on as many questions as possible.

For each of the questions, provide the following: List the research question (be sure to phrase as a measurable question) Identify the variables presented in the question Provide an operational definition for each variable Describe each variable’s scale of measurement (nominal, ordinal, interval, or ratio) and characteristics (i.e., discrete vs. continuous, numerical vs. categorical, etc.)

Replies – Though you may respond to your peers multiple times during the week to provide support or feedback, students are required to respond substantively to at least two of their classmates’ postings by Day 7.

Point Value: 3 Points Click here for instructions on how to participate in this discussion. (Links to an external site.)Links to an external site.

Thursday Sep 13 at 6:12 pm Hi Everyone,
I hope it helps.
Dr. Kathryn ————————————————————————————————————————————-
180918 GR (38) Home Announcements Library Writing Center Writing for Success Modules Grades Tutoring on Demand Week 1 Introduction Introduction Learning Outcomes Overview Resources Introduction: Basic Concepts

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: What is the purpose of studying and understanding statistics, both descriptive and inferential? 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)? How are frequency distributions used to organize and graphically represent data? What can the shape of the frequency distribution tell us about the data? What are the different measures of central tendency and variability? How are they calculated or determined? What are the characteristics of a normal distribution? When and why would we use z scores and means? Learning Outcomes

Upon successful completion of this week, students will be able to: Explain the difference between a sample and the population. (Aligns with CLOs 1) Identify the various attributes of a variable (e.g., discrete versus continuous, quantitative versus categorical, and scale of measurement). (Aligns with CLOs 1) Explain the characteristics and usefulness of a normal distribution. (Aligns with CLOs 1) 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 Recommended References

American Psychological Association (2010). Publication manual of the American Psychological Association (6th ed.). Washington, D.C.: Author.

Cengage Learning (2005). Research Methods Workshops. Available from: http://www.wadsworth.com/psychology_d/templates/student_resources/workshops/resch_wrk.html (Links to an external site.)Links to an external site.

Cengage Learning (2005). Statistics Workshops. Available from: http://www.wadsworth.com/psychology_d/templates/student_resources/workshops/stats_wrk.html (Links to an external site.)Links to an external site.

Coughlan, M., Cronan, P., & Ryan, F. (2007). Step-by-step guide to critiquing research. Part 1: Quantitative research. British Journal of Nursing, 16 (11), 658-663. Retrieved from: http://www.unm.edu/~unmvclib/cascade/handouts/critiquingresearchpart1.pdf (Links to an external site.)Links to an external site.

Easton, V. J., & McColl, J. H. (1997). STEPS: Statistics Glossary v1.1. Retrieved from University of Glasgow Web site: Basic Definitions: http://www.stats.gla.ac.uk/steps/glossary/basic_definitions.html (Links to an external site.)Links to an external site.

Easton, V. J., & McColl, J. H. (1997). STEPS: Statistics Glossary v1.1. Retrieved from University of Glasgow Web site: Presenting Data: http://www.stats.gla.ac.uk/steps/glossary/presenting_data.html (Links to an external site.)Links to an external site.

Easton, V. J., & McColl, J. H. (1997). STEPS: Statistics Glossary v1.1. Retrieved from University of Glasgow Web site: Sampling 1: http://www.stats.gla.ac.uk/steps/glossary/sampling.html (Links to an external site.)Links to an external site.

Easton, V. J., & McColl, J. H. (1997). STEPS: Statistics Glossary v1.1. Retrieved from University of Glasgow Web site: Sampling 2:http://www.socialresearchmethods.net/kb/sampling.php (Links to an external site.)Links to an external site.

Easton, V. J., & McColl, J. H. (1997). STEPS: Statistics Glossary v1.1. Retrieved from University of Glasgow Web site: Descriptive statistics: http://www.socialresearchmethods.net/kb/statdesc.php (Links to an external site.)Links to an external site.

Easton, V. J., & McColl, J. H. (1997). STEPS: Statistics Glossary v1.1. Retrieved from University of Glasgow Web site: Levels of measurement: http://www.socialresearchmethods.net/kb/measlevl.php (Links to an external site.)Links to an external site.

Easton, V. J., & McColl, J. H. (1997). STEPS: Statistics Glossary v1.1. Retrieved from University of Glasgow Web site: Variables: http://www.socialresearchmethods.net/kb/variable.php (Links to an external site.)Links to an external site.

Tufts University (2005). Academic Technology’s ConStats. Sampling Distributions: http://constats.atech.tufts.edu/sampling_DEV.swf (Links to an external site.)Links to an external site.

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