What are the characteristics of a normal distribution


Assignment

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:

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)

Written Assignment

Background

The SMARTLab is a self-paced, online basic statistics course designed to prepare you for your graduate courses and graduate research.

You will use the online primer in addition to this classroom to complete the following lessons.

Access both through the following:

• Constellation: Carruthers, M. W., Maggard, M. (2012). SmartLab: A Statistics Primer. San Diego, CA: Bridgepoint Education, Inc.
• SMARTLab

Complete the SmartLab lessons on Sampling, Variables, Measures of Central Tendency and Measures of Variability.

Assignment Requirements

Complete all components of the lessons on sampling, variables, central tendency, and variability. You may retake the post-tests as many times as you need to earn at least 80%. Once you achieve 80% on the post-tests for each lesson, submit a screen shot of your grading summary.

You also need to include a brief (no more than 350 words) analysis of what you learned from the exercises, what areas you found most difficult, what insights you gained or how you might apply what you learned. Be certain to include a title page with your name, date, instructor, and course title/section. This all has to be completed by Day 7.

Format your assignment according to the following formatting requirements:

1. The answer should be typed, double spaced, using Times New Roman font (size 12), with one-inch margins on all sides.

2. The response also include a cover page containing the title of the assignment, the student's name, the course title, and the date. The cover page is not included in the required page length.

3. Also Include a reference page. The Citations and references should follow APA format. The reference page is not included in the required page length.

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.

Cengage Learning (2005). Statistics Workshops.

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.

Easton, V. J., & McColl, J. H. (1997). STEPS: Statistics Glossary v1.1.

Easton, V. J., & McColl, J. H. (1997). STEPS: Statistics Glossary v1.1. Retrieved from University of Glasgow Web site: Presenting Data.

UIS. (n.d.). How to critique a journal article.

Tufts University (2005). Academic Technology's ConStats. Sampling Distributions.

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