ED 602

Statistical Research for Behavioral Sciences

Brian G. Smith, Ph.D.

 
Instructor: Dr. Brian G. Smith  
Office: Lommen 214 G
Phone: 218 477-5890
Email: smithb@mnstate.edu
Office Hours: Monday and Wednesday -- 10:00am -12:00pm & 1:00pm - 4:00pm
 
Nature of the Course:

This course is designed to help students acquire the necessary statistical skills needed to conduct and be critical consumers of scientific educational research. It is a course aimed at producing careful and accurate researchers as well as astute readers of professional manuscripts and articles from a wide variety of educational settings. The basic areas to be covered in this course will include measurement and descriptive statistics, frequency distributions, measure of central tendency, measures of dispersion, standard normal distributions, and standard scores. The more advanced topics will include correlation, regression, hypothesis testing, “t” tests, and analysis of variance (ANOVA)

 
Structure of the Course:

This is a distance education/online course; most of the material and assessment is on line, but some aspects of the course will require a visit to the mailbox. As an online course, it is possible to take advantage of technology and create a learning environment that allows for variability among students while efficiently covering all the material. The lessons are set up to be completed on a weekly basis-one for each week of a winter/spring semester.

Note: The constructed response quizzes set up by subject area, like Counseling/Student Affairs, or Nursing, are intended to be Homework only. In order for you to see my feedback for each question, I must have you submit it for grading. This resulting "grade" is not downloaded anywhere else. It will NOT count toward your final grade. Only the lesson quizzes, which are multiple choice, count toward your final grade. You may take the lesson quizzes twice, the highest score will be recorded.

The  primary advantage of the course is that you may proceed at your own pace in your chosen location up to the midterm and the final. Midterm and final assessments must done on a print out of the emailed exams since it is extremely cumbersome to "show all of your math work" in a word processing program. When a student has completed the required lessons to take the midterm or final exams, they will be given an email by the instructor with the files attached.

Secondly, this course contains multiple options for the same material presented in ways relevant to the area of study of most of the students. Each lesson contains four different versions of homework: Counseling and Student Affairs; Education Leadership; and Special Education. Each version uses separate samples of homework relevant to that area of study throughout the course. Any student may may do the assignments from any area. It is recommended to try more than one area prior to taking the lesson final quiz.

 
Required Text:

Statistics for the Behavioral Sciences, 6th Ed., Gravetter, Frederick & Wallnau, Larry; Thomson/Wadsworth Publishers, Belmont CA.    ISBN:0-534-60246-0 

 

CONCEPTUAL FRAMEWORK OF THE MSUM TEACHER EDUCATION UNIT

MSUM candidates are professionals who are knowledgeable, reflective, humanistic, and creative.

Knowledgeable: MSUM candidates display competence in their subject matter, built upon a strong grounding in liberal studies. MSUM candidates understand the principles of learning, assessment and technology. They understand and apply legal and ethical considerations to all aspects of their work. MSUM candidates are able to integrate theory and practice, and view learning as an active process. MSUM candidates demonstrate the ability to model connections between philosophical foundations and best practices in the field. As life-long learners, MSUM candidates engage in research and complex thinking. They design opportunities for others to seek knowledge and to understand themselves as members of the world community.

Reflective: MSUM candidates engage in thoughtful analysis of the meaning and significance of their actions, decisions, and results with regard to their work in order to assess progress in meeting this guiding principle. It is through this reflective process that candidates improve instruction, implement new ideas, abandon ineffective methodologies, and enhance learning outcomes for their students. MSUM candidates are skilled at analyzing their teaching from a variety of perspectives and identifying connections between teaching strategies and student learning. In addition, candidates utilize a variety of techniques to question their procedures and consider alternatives for instruction and student growth. MSUM candidates recognize learning, motivational, and developmental variables and relate those dimensions to their teaching practices. Finally, MSUM candidates bring a questioning spirit to received wisdom and conventional practice when needed.

Humanistic: MSUM candidates value the personal worth of each individual. This is based on a belief in people's potential and innate ability to develop to their fullest. MSUM candidates' actions are grounded in knowledge of different cultural and ethnic groups within the world community, and in knowledge of the influence of culture and history, ethnicity, language, gender and socio-economics on one's life. This knowledge base informs candidates' decision-making as they create environments that promote freedom, compassion, and success for all learners. MSUM candidates are fair-minded in their interactions with others, as well as sensitive to and accepting of individual differences. Further, MSUM candidates have an understanding of aesthetics and the diversity that is part of the human experience and will incorporate this knowledge into their work. MSUM candidates recognize and accommodate a variety of linguistic and nonlinguistic interpersonal skills in their actions with others. MSUM candidates foster resiliency in the students with whom they work and model these qualities in their own work.

Creative: MSUM candidates understand the powerful resources of the arts and sciences and use their knowledge of these areas to bring the best of their imaginative and creative acts into the classroom. MSUM candidates recognize the important role creativity plays in the design of instruction and classroom environment. They will, for themselves and for their students, meet new situations with resourcefulness, excitement and curiosity, with an investigative attitude, and with the ability to pose, seek and design solutions to problems. MSUM candidates are cognizant of the aesthetic elements of the world and draw on that knowledge to make curricular decisions designed to help students not only learn about aesthetics, but to also learn how to think about the world at large.

 

Graduate Expectations:

It is expected that this course will challenge the participant to expand their present and past experiences in the field of education to include a scientific approach to their field. This course should build on and be integrated into the program courses and field research of each participant’s advanced degree program. A scientific approach to research is fairly rigid with specific procedures designed to investigate professional questions that grow from practitioner observations. It is this inquisitiveness that will be maximized in this course. Prior knowledge of statistics is not necessary. An open mind is necessary.

 

Course Objectives:
The curriculum and methods of instruction are carefully selected to facilitate the acquisition of the following learning objectives:

  • Understand the basic statistical tools that are commonly used in educational research.
  • Know the appropriate methods for analyzing statistical data.
  • Recognize situations in which parametric or nonparametric tests should be applied.
  • Know how to conduct some specific parametric and nonparametric tests.
  • Be able to employ statistics in order to answer specific research questions.
 

 

Grading:
 
Quizzes 20%
Midterm 40%
Final Exam 40%

 

 
 

Special Accommodations:
Special accommodations can be made for students who have disabilities that represent a barrier to full participation in this course. If you think you may have a disability, please contact the instructor at your convenience for consultation. Keep in mind, however, that this is an on line course, and accomodations may be limited. This course is also offered in a regular classroom setting.

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Course Outline:

Lesson
Topic of Study
Readings
Objectives
1
Intro, Why Stats, Why Ed Research Chapter 1 * Understand what is Statistics.
* Understand why Statistics are necessary.
2
Basic Concepts and Symbols in Stats Chapter 1 * Understand the science of Statistics.
* Define populations and samples.
* Describe various sampling methods.
* Detect biases in samples.
3
Ethical issues in Stats and Research Web Based * Understand the ethical issues involved in statistics and research.
* Critically examine existing research.
4
Freq. Dist., %tile ranks, graphing Chapter 2 * Create frequency distributions of grouped and ungrouped scores.
* Present frequency distributions graphically.
* Analyze shapes of frequency distributions.
* Calculate percentiles and percentile ranks
5
Measures of Central Tendency Chapter 3 * Calculate the mode, median and mean of a sample.
* Compare the mode, median and mean of a sample.
* Draw conclusions about a sample from comparisons of the mode, median, and mean.
6
Measures of Variability Chapter 4 * Calculate various range measures of a sample.
* Calculate the Standard Deviation of a sample.
* Calculate the Variance of a sample.
* Draw conclusions about a sample based on measures of variability.
7
Normal Curve, Standard Scores Chapter 5 * Understand the concept of a normal distribution.
* Draw and label a standard normal curve.
* Calculate a z-score.
* Calculate the percentage of scores above or below a given score.
Midterm
 
On Campus
8
Correlation Chapter 16 * Draw scatterplots.
* Discuss the relationship between 2 variables based on the scatterplots.
* Calculate the Pearson Correlation Coefficient (Pearson r) for 2 variables.
* Test the statistical significance of the Pearson r.
* Report the results of a correlational study in laymanís terms.
* Calculate the Spearman rank-order correlation coefficient for curvilinear relationships.
9
Regression Chapter 17 * Plot a regression line.
* Predict scores from a regression line.
* Calculate the amount of error in a prediction from a regression line.
* Discuss how the concept of regression toward the line affects predicted scores.
10
Inferential Statistics Chapter 7 * Calculate the standard error of the mean.
* Understand the difference between mathematical difference and statistically significant difference between means.
* Use the z-test to test a hypothesis
11
One sample T- Tests and Confidence Intervals Chapter 9 * Use a one sample t-test for testing a hypothesis.
* Report findings from a t-test in an appropriate format.
* Construct confidence intervals for a population mean.
* Interpret t-test results in a clear and concise manor.
12
Two group T- Tests Chapter 10 * Describe the basic research process.
* Use a two sample t-test for hypothesis testing.
* Understand the concept of power in statistics.
* Understand the difference between Type I and Type II errors.
13
One factor ANOVA (between subjects) Chapter 13 * One factor ANOVA between subjects
 
Final Exam
 
On Campus
 This is meant as a roadmap for the course. Changes may be made without notice.
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