CRJ/SOC/SWK 360 Social Statistics Syllabus, Fall 2008
Professor: Stephen M. Marson, Ph.D., ACSW

Office: 217 BA; Phone: 521-6475; Inclement weather: (910) 521-6888

COURSE OUTLINE AND COURSE OBJECTIVES
The course will come from the material in Chapters 1 - 8 of the text. In addition, we will be watching some of the films from the series Against All Odds: Inside Statistics (you may use the hot link to obtain the library call number for the films)    The course outline follows the sequence of material addressed in the course objectives.  The course objectives are building blocks.   Thus, competence for each course objective is dependent on the students understanding of the previous objective.   Upon completion of this course, the students should be able to think critically about data, to select and use graphical and numerical summaries, to apply standard statistical procedures, and to draw conclusions from such analysis.

1. To understand basic statistical symbols.
2. To be able to picture and understand the shape of a distribution (central tendency and spread) by using a histogram , a stemplot, and a box plot.
3. To understand and calculate measures of central tendency including median, mean, mode, harmonic mean, and geometric mean, and related concepts of quartiles, range, z-score and standard deviation.
4. To understand the notion of level of measurement including concepts as nominal, ordinal, interval, ratio, discrete, and continuous data
5. To understand the concept of "distribution" which includes density curves, normal curves, the 69-95-99.7 rule and the standardization rule.
6. To understand and calculate relative frequencies, percentiles and quartiles.
7. To appreciate the use of time series analysis by understanding seasonal variations and the process of smoothing data (especially, Moving Averages and Running Medians).
8. To test and understand the concept of independence and autocorrelation (formula in MS Word 97, it works best by using Explorer -- not Netscape) for time-series analysis.
9. To understand growth patterns particularly linear and exponential growth.
10. To be able to analyze the relationship between two variables using a scatterplot and by adding an addition variable.
11. To be able to interpret and calculate correlation and appreciation its relationship to regression.
12. To understand and apply the rules for establishing a causal relationship by analyzing associations and using Simpson's Paradox.
13. To be able to use and understand experimental designs by comparing them to observational studies, appreciating confounding factors, and accepting the importance of randomization.
14. To understand how complex surveys are designed and how sampling effect distributions.
15. To understand and apply probability rules (including the addition and multiplication rules).   For further information see Diaconis .
16. To understand the fundamentals of control charts and time series analysis particularly the rules for control charts.
17. To understand the use of binomial distributions and the law of large numbers.
18. To understand the central limit theorem.
19. To understand and calculate confidence intervals for samples.
20. To understand the purpose of a significance test, type I/type II errors, P-values, and statistical significance.
21. To understand and apply t-procedures for single and paired comparisons.
22. To compare two means, two samples by using the t-test.
23. To be able to produce an inference for proportions and two-way tables.
24. To understand and apply c² test and distribution.
25. To have the basis for understanding and producing an inference for linear regression.
26. To understand the difference between statistical and practical significance.

Handouts:
• Addition and Multiplication Rules (MS Word -- use Explorer for best results)
• Anorexia Homework (Must use Excel)
• Solitaire and probability (PowerPoint Presentation)
• Data Sheet for many homework assignments (MS Word landscape, legal size paper -- use Explorer)
• THE GENERAL INTERPRETATION OF r (MS Word -- use Explorer for best results)
• Formula for autocorrelation (MS-Word 2000 -- use Explorer for best results)
• Critical Values Chart for autocorrelations t-test (MS-Word 97 -- use Explorer for best results)
• Flowchart for making decisions about SSDs (MS-Word 97 -- use Explorer for best results)
• MAT or FDT Method:  Which to use? (MS-Word 97 -- use Explorer for best results)
• Data transformation MAT and FDT (MS-Word 97 -- use Explorer for best results)
• Z-score (MS-Excel -- use Explorer for best results)
• Home work for autocorrelation and 2SD approach (MS-Excel -- use Explorer for best results)
• t-test home work  (Works best with Netscape)
• Additional chapters to read (must use Adobe Acrobat Reader)
  • Chapter 26 -- Nonparametric Statistics
  • Chapter 27 -- Statistical Process Control (Key importance for nurses and social workers)
  • Chapter 28 -- Multiple Regression

Exams: Open book exams will be given on the following dates: September 10, October 1, October 29, November 19 and December 8 or 10 (will discuss in class) Each student will get immediate feedback and will be given an opportunity to raise one's grade by ½ credit for each item that is successfully corrected. The final exam will also provide immediate feedback and raise one's grade by a ½ credit for each item. Students who do not complete the feedback assignment in a timely manner will not receive full credit.   Students who do not submit corrections (including the final) will be dropped one letter grade for that exam.  Working on the problems that were found to have incorrect answers is an extremely important part of the learning process.  If a correct answer is mark wrong, write an explanation.  If the student is correct, the student will gain FULL credit.

Attendance Policy:  Missing 6 hours of class constitutes an F. Don't miss class, don't be late. See Program's Attendance Policy.  The good news is, students can attend either section.   Both sections cover the same material.  Thus, if you can't attend the section in which you are enrolled, you may attend the other section and not be penalized.


Homework: Assignments from the workbook, text, collected data other problems will be given daily. Assume that students will be given a homework assignment every day.


Tutoring:   In addition, tutoring services are available at the UNCP campus.  Contact Student Support Services for more information.


Grading: All exams including final will receive an equal weight which will equal a total of 90% of the final grade. The combination of class participation and homework will equal 10% of the final grade (5% for each) and will be used in borderline cases.

A 92-100	B 82-86	C 72-76	D 62-66
A- 90-91	B- 80-81	C- 70-71	D- 60-61
B+ 87-89	C+ 77-79	D+ 67-69	F 0-59


Text: The Basic Practice of Statistics  (Required) and A Study Guide for Moore’s Basic Practice of Statistics  (Not Required) by David S. Moore


Suggested References:
Napier, A., Judd, P. J. & Rand, B. (2002). Mastering and Using Microsoft Excel 2002. Boston, Thomson Learning.
Berk, K.N. & Cary, P. (1998). Data Analysis with Microsoft Excel. Pacific Grove, CA: Duxbury.
Middleton, M. R. (2003). Data Analysis Using Excel. Pacific Grove, CA: Duxbury.


Statistical Dictionaries:
http://www.uvm.edu/~dhowell/StatPages/Fundamentals/Glossary.html,
http://www.stats.gla.ac.uk/steps/glossary/alphabet.html,
http://linkage.rockefeller.edu/wli/glossary/stat.html,
http://www.oswego.edu/~kane/econometrics/glossaries.htm,
http://www.xrefer.com/search.jsp


Calculator Recommentation: In my experience, I found that the Sharp Corporation offers the best Scientific Calculators.   One way of testing a calculator is by finding the square of -5.   If your answer is -25, don't purchase the calculator.   A list of features for good calculators for this course can be found at: Scientific Calculators.   If you click on the gold ">>" sign, you'll get detailed information about special features.   If you would like to find a calculator with special features click here: Special Features.

Students with Disabilities: Any student with a documented disability needing academic adjustments is requested to speak directly to Disability Support Services and the instructor, as early in the semester (preferably within the first week) as possible. All discussions will remain confidential. Please contact Disability Support Services, DF Lowry Building, 910-521-6695.

Cell Phone Policy: Students are not permitted to conduct phone conversations during class time.  Students are not permitted to have cell ring during class time.   Students who use conduct a phone conversation or allow their phones to ring during class time will be drop 10 points on the next quiz or 5 points for their final exam.   During an exam, phones and hand held computers are not permitted in the room.
 

BIBLIOGRAPHY
General References
• Bloom, M., Fischer, J. & Orme, J. G. (1999). Evaluation Practice. Boston: Allyn and Bacon.
• Chambers, J.M. (1983). Graphical methods for data analysis. Belmont, Calif.: Wadsworth. QA276.3 .G73 1985
• Charts, Graphs and Stats Index. (1988/1991). Fort Atkinson, Wis.: Highsmith Press, 1992. AI3 .C43 1988-91
• Gordon, S. & Gordon, F. (1992). Statistics For The Twenty-First Century. Washington, D.C.: Mathematical Association of America. HA35 .S72 1992
• Hoaglin, D C. & Moore D. S. (1992). Perspectives On Contemporary Statistics. Washington, D.C.: Mathematical Association of America. QA276.18 .P47 1992
• Jaisingh, L. R., (2000). Statistics for the Utterly Confused. New York: Graw-Hill.
• Kanji, G.K. (1993). Statistical Tests. Thousand Oaks, CA: Sage. Ref QA 277.K35 1995
• Kendall, M. G. (1986). A Dictionary of Statistical Terms. New York: the International Statistical QA276.14 .K46 1986
• Knapp, T. R. (1996).  Learning Statistics Through Playing Cards. Thousand Oaks, CA: Sage Publications. QA 276.12  .K597 1996.
• Kruskal W.H. and Tanur, J. M. (1978). International Encyclopedia Of Statistics. New York: Free Press, 1978. HA17 .I63 v. 1 HA17 .I63 v. 2
• Kurtz, A. K. (1967). Statistical dictionary of terms and symbols New York, Hafner Pub. Co. HA17 .K83 1967
• Madison, B. L. (1990). A Challenge Of Numbers. Washington, D.C. : National Academy Press, 1990. QA13 .M14 1992
• Marriott, F. H. C. (1991). A Dictionary Of Statistical Terms. Burnt Mill, England: International Statistical Institute. HA17 .K4 1991
• Moore, D. (1997). Statistics: Concepts and Controversies. New York: Freeman.
• Owen, D. B. (1962). Handbook Of Statistical Tables. Reading, Mass., Addison-Wesley. HA48.O9
• Phillips, J. L., (1988). How to Think About Statistics New York : W.H. Freeman. HA29 .P517 1988
• Rowntree, D. (1981). Statistics Without Tears: A Primer for Non-mathematicians / New York : Scribner QA276.12 .R68 1981
• Ryan, J. M. (1991). Handbook Of Statistical Procedures And Their Computer Applications To Education And The Behavioral Sciences. New York: American Council on Education LB1028.R93 1991
• Schmid, C.F. (1983). Statistical Graphics: Design Principles And Practices New York : Wiley. QA276.3 .S35 1983
• Sen, P. K. (1989). Beyond The Traditional Frontiers Of Statistical Sciences. Chapel Hill, N.C. : Dept. of Biostatistics, University of North Carolina at Chapel Hill. NC Documents-Fiche G68 3:1861
• Tufte, E. R. (1983). The Visual Display Of Quantitative Information. Cheshire, Conn: Graphics Press, 1983. QA276.3 .T83 1985
• Tufte, E. R. (1990). Envision Information. Cheshire, Conn: Graphics Press.
• Tufte, E. R. (1997). Visual Explanations: Images and Quantities, Evidence and Narrative. Cheshire, Conn: Graphics Press.
• White, J. V. (1984). Using Charts and Graphs: 1000 Ideas for Visual Persuation. R.R. Bowker Company.


References that influence the direction of this course (books used while I was a student)

• Andrews, F. M. et al., (1981). A Guide for Selecting Statistical Techniques for Analyzing Social Science Data. Ann Arbor, MI: University of Michigan, Survey Research Center.
• Blalock, H.M. (1997). Social Statistics. New York: McGraw-Hill.
• Bohnrnstedt, G.W. & Knoke D. (1982). Statistics for Social Data Analysis. Itasca, Il: F.E. Peacock.
• Glass, G.V. & Stanley, J. C. (1970). Statistical Methods in Education and Psychology. Englewood Cliffs, NJ: Prentice Hall.
• Campbell, D.T. & Stanley, J.C. (1963). Experimental and Quasi-Experimental Designs for Research. Chicago: Rand McNally.
• Kluch, H. E. (1970). Statistics: The Essentials for Research. New York: John Wiley.
• Keppel, G. (1982). Design and Analysis: A Research Handbook. Englewood, Cliffs, NJ: Prentice Hall.
• Loether, H.J. & McTavish, D.G. (1980). Descriptive and Inferential Statistics: An Introduction. Boston: Allyn and Bacon.
• Mendenhall, W., Ott, L., & Larson, R.F. (1974). Statistics: A Tool for the Social Sciences. Belmont, CA: Wadsworth.
• Siegal, S. & Castellan, N.J. (1988). Nonparametric Statistics for the Behavioral Sciences. New York: McGraw-Hill.
• Tabachnick, B. G. & Fidell, L. S. (1983). Using Multivariate Statistics. New York: Harper & Row.