Basic Statistics

Course Prefix/Number:

EDFN 7304

Course Title:

Basic Statistics

Instructor Name and Contact Information

Dr L. Carolyn Pearson
Professor and Coordinator of Educational Foundations
Office:  Dickinson Hall, Room 419F
Phone: 501-569-3553
FAX: 501-569-3547
Email:  lcpearson@ualr.edu
Office Hours: Tuesday 10-3

Prerequisites:

N/A

Course Description:

The course is designed as an entry level course in statistics and covers both descriptive and inferential statistical techniques to solve applied research problems. Emphasis is also placed on using statistical software packages and will cover the most widely used statistical procedures in education, particularly SPSS.

Student Learning Outcomes:

Upon completion of the course students should be able to demonstrate:

1.     The selection of an appropriate statistical technique to be utilized when collecting and analyzing data within an educational setting.

2.     The ability to utilize descriptive and inferential statistics when examining the relationships between variables that are generated from school-based data.

3.     The ability to determine if statistical techniques used in current educational research studies are consistent with the problem of the study, and as a result, demonstrate the relevance of the study in an applied school setting.

Course Objectives

Scaling, normalized data and distributions, and descriptive statistics

1.     Describe the characteristics of nominal, ordinal, interval, and ratio scales.

2.     Describe the concepts of the normal curve and positively and negatively skewed distributions.

3.     Given a set of educational data, calculate and be able to describe various descriptive statistics (e.g., mean, median, mode range, variance, standard deviation, various correlation coefficients).

4.     Describe and be able to perform data transformations (e.g., scores that have been manipulated by a constant).

5.     Be able to provide a correct interpretation of standard scores.

6.     Given a set of educational data, be able to use various current statistical software packages (e.g., SPSS or SAS) to produce normalized or descriptive data.

Inferential statistics

1.     Given appropriate educational data, calculate the area (probability) above or below any point, or between any two points, under the normal curve.

2.     Identify various statistics and their corresponding population parameters.

3.     Describe Type I and Type II errors, power, and effect sizes.

4.     Describe the Central Limit Theorem.

5.     Distinguish between correct and incorrect interpretations of a confidence interval.

6.     Distinguish between a statistical or research hypothesis and the interpretation of statistical significance in hypothesis testing.

7.     Given a description of the question to be investigated, identify the statistical hypothesis to be tested, the correct critical value from the appropriate table, and the appropriate computational formula.

8.     Perform the statistical test required and make a correct hypothesis decision.

9.     Given a set of educational data, be able to use various current statistical software packages (e.g., SPSS or SAS) to perform various inferential tests.

General Linear Model

1.     Given a set of educational data, calculate either a simple or multiple linear regression equation and its corresponding standard error of estimate.

2.     Describe explained and unexplained variance.

3.     Test the significance of the overall regression effect, the slope(s), and the partial and semipartial correlation coefficients of a regression equation.

4.     Given student scores on a dependent variable for subjects assigned to several levels of an independent treatment) variable, perform an ANOVA and the appropriate post-hoc test.

5.     Given a set of educational data, be able to use various current statistical software packages (e.g., SPSS or SAS) to perform ANOVA the corresponding appropriate post hoc test.

Texts and Software:

Required:

Coladarci, T., Cobb, C. D., Minium, E. W., & Clarke, R. C. (2008). Fundamentals of statistical reasoning in education, 2nd Edition. Hoboken, NJ: John Wiley & Sons.  ISBN10:  0-470-08406-5 or ISBN13:  978-0470-08406-9

SPSS graduate package software. I would recommend that you do not buy the student version of SPSS for this course if you are going on to the intermediate course, buy the graduate pack version (full-blown capability) so that you can run the necessary and more advanced syntax files that I post in that class. Where to buy? Well, this one always seems to be a shifting target, so go on the web and start looking and let each other know via the course listserv if you find a good deal.

Recommended:

Green, S. B., & Salkind, N. J. (2008). Using SPSS for Windows and Macintosh: analyzing and understanding data (5th ed.). Upper Saddle River, NJ: Pearson Prentice Hall.  ISBN13: 978-0-13-189025-1 ISBN10: 0-13-189025-5

Grading/Evaluation:

Each student is expected to read and carefully study the reading assignments in the text and on the website.  In addition, the student is encouraged to do a sufficient number of practice exercises that are found in each weeks instruction in the website and at the end of each chapter in the text in order to help achieve a greater understanding of the concepts. All assignments, threaded discussions, and exams are done in Blackboard according to the dates that are published on the course schedule. As for Blackboard, you will not be given the opportunity to complete an assignment and receive credit outside of the "window" in which the assignment is posted and viewable. Of the graded assignments, which are also in Blackboard, I do drop the lowest grade when averaging at the end of the term; also, I do not give course incompletes unless there is a documented severe medical excuse. Weighting assigned to each of these components for computation of the final grade is as follows:

Grading Policy:

References:

        Freed, M.N., Ryan, J.M., & Hess, R.K. (1991). Handbook of statistical procedures and their computer applications to education and the behavioral sciences. NY: MacMillan Publishing Co.

        Kennedy, J.J., & Bush, A. J. (1985). An Introduction to the Design and Analysis of Experiments is Behavioral Research. NY: University Press of America.

        Marascuilo, L., & McSweeney, M. (1987). Nonparametric and distribution-free methods for the social sciences. CA: Brooks/Cole Pub. Co.

        Pedhazur, E.J. (1992). Multiple Regression in Behavioral Research. (2nd Ed.) NY: CBS College Publishing.

        Shavelson, R. (1988). Statistical reasoning for the behavioral sciences, MA: Allyn & Bacon.

Special Technology utilized by Students:

Students will need access to Adobe Acrobat Reader^© (version 9 or higher) to open PDF files that are used during the course.
Students will need access to an Internet browser that has JavaScript enabled.
Students must be able to complete online forms to participate in threaded discussions.
Students will need access to a computer that is capable of running SPSS for Windows^©.

Expectations for Academic Conduct/Plagiarism Policy:

As members of the University of Arkansas at Little Rock, we commit ourselves to honesty. As we strive for excellence in performance, integrity—personal and institutional—is our most precious asset. Honesty in our academic work is vital, and we will not knowingly act in ways which erode that integrity. Accordingly, we pledge not to cheat, nor to tolerate cheating, nor to plagiarize the work of others. We pledge to share community resources in ways that are responsible and that comply with established policies of fairness. Cooperation and competition are means to high achievement and are encouraged. Indeed, cooperation is expected unless our directive is to individual performance. We will compete constructively and professionally for the purpose of stimulating high performance standards. Finally, we accept adherence to this set of expectations for academic conduct as a condition of membership in the UALR academic community.

Disability Support Services

It is the policy of the University of Arkansas at Little Rock to create inclusive learning environments. If there are aspects of the instruction or design of this course that result in barriers to your inclusion or to accurate assessment of achievement–such as time-limited exams, inaccessible web content, or the use of non-captioned videos–please notify the instructor as soon as possible. Students are also welcome to contact the Disability Resource Center, telephone 501-569-3143 (v/tty). For more information, visit the DRC website at at http://ualr.edu/disability/.