Office Hours:   by appointment; 
 Course Prerequisite: MAT 105 or 107

Office: Sampson 221; Phone: 521-6475; Inclement weather: (910) 521-6888

 

Table of Contents
Academic Honor Code Dictionaries Handouts  Staight Suggested References

Attendance

Exams

 Homework

Text

Calculator

 Final Exam Process 

Phoning Policy

Tutoring

Course Objectives

Disabilities

References

Scoring the Stress Index

Course Outline

Grades

Solitaire Rules

Software

 

 

  


    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.

     

    Readings

     Course Competencies 

    See hot links

    Powerpoints

       1. To understand basic statistical symbols. (for the projector)  To understand what type of chart (line, pie or bar) to employ in relationship to the data.

    Chap 1

       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.

    Chap 2 & 3

       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.

    See hot link >

       4. To understand the notion of level of measurement including concepts as nominal, ordinal, interval, ratio, discrete, and continuous data

    Chap 3

       5. To understand the concept of "distribution" which includes density curves, normal curves, the 69-95-99.7 rule and the standardization rule. 

    Chap 3

       6. To understand and calculate relative frequencies, percentiles and quartiles.

    Chap 11, 26

       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).

    Chap 4

       8. To understand growth patterns particularly linear and exponential growth.

    Chap 4 & 5

       9. To be able to analyze the relationship between two variables using a scatterplot and by adding an addition variable. 

    Chap 5

    10. To be able to interpret and calculate correlation and appreciation its relationship to regression.
    Chap 5 11. To understand the interpretive differences between r and the standard deviation of the residuals

    Chap 6

    12. To understand and apply the rules for establishing a causal relationship by analyzing associations and using Simpson's Paradox.

    Chap 8, 9

    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.

    Chap 9

    14. To understand how complex surveys are designed and how sampling effect distributions.

    Chap 10, 11, 12

    15. To understand and apply probability rules (including the addition and multiplication rules).   For further information see Diaconis . In class assignment.

    Chap 13

    16. To understand the use of binomial distributions and the law of large numbers.

    Chap 11

    17. To understand the central limit theorem.
    See hot links > 18. 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. 1

    Chap 15

    19. To understand and calculate confidence intervals for samples.

    Chap 15, 16, 17

    20. To understand the purpose of a significance test, type I/type II errors, P-values, and statistical significance.

    Chap 18

    21. To understand and apply t-procedures for single and paired comparisons.

    Chap 19

    22. To compare two means, two samples by using the t-test.

    Chap 20-21

    23. To be able to produce an inference for proportions and two-way tables.

    Chap 23

    24. To understand and apply c2 test and distribution.

    Chap 24

    25. To have the basis for understanding and producing an inference for linear regression.

    See hot link >

    26. To understand the difference between statistical and practical significance.


    Handouts:


Exams: Open book exams will be given on the following dates: July 5, 12, 19 and Aug 2 (dates may change). 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 zero for that exam and not be permitted to take the next 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:  There are no excused absences.  Students are therefore encouraged to be mindful of absences and make every effort to be in attendance. Students are expected to have read assigned material prior to the class. Students are also expected to participate in class discussion, exercises and any Blackboard discussions that may be announced.  Students are considered in attendance only if present for the entire class. Arriving late or leaving early is disruptive will be dealt with by the instructor.  Attendance will be used as a criterion in determining the final grade.  (Present 1 point; Tardy 1/2 point; Not present 0 points)  For more details see “Class Attendance” in The University of North Carolina at Pembroke Student Handbook.

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 80% of the final grade. Attendance and class participation are constitute 10% and home is worth 10%.

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 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.stats.gla.ac.uk/steps/glossary/alphabet.html,
http://linkage.rockefeller.edu/wli/glossary/stat.html,
http://www.oswego.edu/~kane/econometrics/glossaries.htm


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.

 

Religion Statement: The University of North Carolina at Pembroke has a legal and moral obligation to accommodate all students who must be absent from classes or miss scheduled exams in order to observe religious holidays; we must be careful not to inhibit or penalize these students for exercising their rights to religious observance.    To accommodate students’ religious holidays, each student will be allowed two excused absences each semester with the following conditions:
1. Students, who submit written notificationto their instructors within two weeks of the beginning of the semester, shall be excused from class or other scheduled academic activity to observe a religious holy day of their faith. Excused absences are limited to two class sessions (days) per semester. 

2. Students shall be permitted a reasonable amount of time to make up tests or other work missed due to an excused absence for a religious observance.

3. Students should be not  be penalized due to absence from class or other scheduled academic activity because of religious observances.

A student who is to be excused from class for a religious observance is not required to provide a second-party certification of the reason for the absence.   Furthermore, a student who believes that he or she has been unreasonably denied an education benefit due to religious beliefs or practices may seek redress through the student grievance procedure,

 

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.  

 

Office of Academic Excellence

Tutoring is available by subject with peer tutors who show proficiency in courses and have been trained in effective tutoring strategies.  The tutoring sessions can host up to five students per session.  To get the most effective results students should sign up for tutoring as soon as possible.  Students should also come to tutoring sessions with specific questions prepared regarding course material.  The more consistent the attendance to tutoring sessions, the better students will understand the material and perform at a higher level in class.  Sign up for tutoring in the Center for Academic Excellence office.

 Supplemental Instruction (SI) is available to assigned classes that present historically difficult material.  An SI Leader is an upperclassman, model student who has taken the course and shown proficiency, and has been trained in effective Supplemental Instruction leadership strategies.  An SI Leader is assigned to the course to attend all lecture sessions and host at least three study sessions per week for students to attend voluntarily.  SI sessions will provide supplemental material for students to use to improve their understanding of the course material.  SI sessions also provide an opportunity for students to ask questions, and gain insight from their classmates.  Students are encouraged to attend as frequently as possible to review the class material consistently.  The more frequent the attendance at SI Sessions, the better students will understand the material and perform in class.

The Resource Learning Lab offers computer based, self-paced tutoring in basic writing skills from composing sentences, paragraphs, and essays, to addressing common writing problems, basic reading comprehension, and word problem dissection.  These programs are 4 – 8 weeks long and offer non-credit, collectable test performance data on each student during their progression through our programs. The Resource Learning Lab also offers tutoring that improves academic study skills through self-help DVD’s, such as Values and Goals, Time Management, Critical Thinking and Problem-Solving, Active Listening and Note-Taking, Researching, Reading and Writing, and Studying and Test-Taking.  These programs are designed to enhance college-level reading comprehension and writing skills, and to improve the areas where students find they have deficiencies.  The Resource Learning Lab is available to all students, whether right out of high school or non-traditional students needing a refresher.
    BIBLIOGRAPHY
      General References
    • Bloom, M., Fischer, J. & Orme, J. G. (2010). 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

    • Gwet, K. (2001). Handbook of inter-rater reliability. Gaithersburg, MD: STATAXIS..

    • 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
    • Kazdin, A. E. (2011). Single-case research designs. NY: Oxford University Press.
    • 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.
    • Williams, F. (2000). Reasoning with Statistics. Belmont, Calif.: Wadsworth.


    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.
    • Noether, G. E. (1990). Introduction to Statisics: The Nonparametric Way. NY: Springer.
    • 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.