Syllabus for Soc 253 (3 hours) / Math 314 (4 hours)

SPRING 2006   On-line course offering

                       

INSTRUCTOR:                        Dr Jim Taulman, Mike Fredenberg

OFFICE LOCATION:              Pine Ridge, Wanblee, Martin, Piya Wiconi     

HOURS:                                   Regular class time or by appointment

OFFICE PHONE:                     605-455-6003

E-MAIL:                                  jtaulman@olc.edu, mfredenberg@olc.edu

                                               

Soc 253 / Math 314 will be offered concurrently as an on-line course. 

 

Soc 253 Catalog Description:             This course provides an introduction to statistics. On successful completion of the course, the student should be aware of common descriptive statistics and graphical procedures. The student should develop an understanding of the basics of statistical inference, be aware of some common inferential statistical procedures used in the social sciences and the environmental sciences, and be able to read and interpret statistical information. Prerequisites: Math 103 with a grade of B or higher.

 

Math 314 Catalog Description: Topics include samples, populations, distributions, descriptive statistics, probability and statistical inference, experimental design, correlation and linear regression.  A lab portion of the course will introduce students to the use of computer-based statistical programs to solve problems in elementary statistics.

 

Required Text:           Brase & Brase (2004). Understanding Basic Statistics, 3rd edition. Houghton Mifflin.

 

Online Materials:  This class will be offered on the Internet via the Moodle interface.  All class assignments and announcements will be posted on this site.  It is imperative that a student check this site daily as the calendar may change at any time.  Students will work with the ExcelŽ spreadsheet program available on all computers in the lab.  On-line tutoring is offered through the Houghton Mifflin Website (www.smartthinking.com/houghton.html).

 

Reading Level:  Students will be expected to read all sections covered in lectures.  The

reading level of the text is grade 14 as computed using the Fry Readability Index.

 

Writing Expected:  Exams and homework assignments may contain essay questions.  

Written reports may be assigned.

 

Critical Thinking: Critical thinking and reasoning are part of any well rounded

education.  This course will supplement these skills whenever possible.  Various

modules and projects will cover this area independent of the course content.

 

Lakota Perspective:  The Lakota perspective will be provided by way of daily

interaction between student and teacher where traditional Lakota values such as patience,

respect, and honor will be maintained.  The students will be expected to aid the teacher

with the inclusion of the Lakota perspective.

 

Course goals: Students who have successfully completed this course will:

1.      Read and interpret statistical results as reported in research articles.

2.      Correctly use descriptive and basic inferential statistical terminology in writing.

3.      Use descriptive and graphical procedures to organize and present data summaries, including measures of central tendency and dispersion, histograms, box plots, and exploratory graphical techniques.

4.      Apply the concept of probability, and describe the meaning of probability and uncertainty in statistical discourse.

5.      Apply the logic of statistical inference, and describe the assumptions on which frequently encountered inferential techniques are based. Apply and interpret the concept of statistical significance.

6.      Apply inferential techniques using z and t tests of significance, including analysis of variance and linear model designs.

7.      Apply correlation procedures to appropriate problems.

8.      Use Excel to apply statistical procedures. Interpret output appropriately and write up results narrative.

 

Methods of Instruction:   This course will be offered on-line with regular meetings in person with instructors for additional assistance.

 

Course Requirements and Assignments:  Regular attendance is vital to successful completion of this course.  Attendance will be based solely on a student successfully submitting weekly  assignments to the instructor.  Oglala Lakota College attendance policy (refer to OLC College Catalog 2005-2006, page 13) will be followed in this course.  A student may be dropped from this course after three consecutive absences and will be dropped after five total absences.  It is the student's responsibility to submit assignments in a timely manner.   

 

Assignment and Grading: The weekly assignment will consist of a written assignment and an on-line quiz. The weekly quiz must be completed within a week of the quiz being assigned.  For the written assignment credit will be given for the approach that is used as well, as for the correct answer.  Therefore, students are strongly encouraged to complete homework legibly and in a manner that a casual observer can understand how an answer was derived.

Grades will be determined from total points for all work as follows:


Homework:       80 points/week =   1200 points

Participation:     20 points/week =     300 points

Weekly Quiz:    100 points/week = 1500 points

Midterm Exam: 1000 points                   

Final Exam:       1000 points

 

Total: 5000 points

 

 A 90-100%

 B 80-89%

 C 70-79%

 D 60-69%

 F 59 or less %


Schedule of classes                                                                                                       Chapter

 

Week 1 , Jan. 24            Statistical concepts and terminology                                            1

 

Week 2 , Jan. 31            Data organization, charts and graphs                                           2

 

Week 3, Feb. 7             Central tendency of data                                                                        3

 

Week 4 , Feb. 14           Measures of variation                                                                3

 

Week 5, Feb. 21            More variation                                                                           3

 

Week 6 , Feb. 28           Probability distributions                                                              5 and 6

 

Week 7 , Mar. 7                        The normal distribution                                                               7

 

Week 8 , Mar. 14           More about the normal distribution                                              7

 

Week 9 , Mar. 21           Sampling distributions                                                                 8

 

Week 10, Mar. 28         Estimation of the mean and other data parameters                       9

 

Week 11, Apr. 4            Hypothesis testing                                                                     10

 

Week 12, Apr. 11          Regression and correlation                                                         4

 

Week 13, Apr. 18          Inferences about paired differences                                            11

 

Week 14, Apr. 25          Means testing                                                                            11

 

Week 15, May 2            Chi square and goodness of fit of sample data to a model             12

 

Week 16, May 9            Final exam