# BSAD/PSYC/POLS 239 – Statistics for Social Sciences

**Latest Course Offering**: Summer 2011, Term 5

**Course Time**: Monday and Wednesday, 5:45 – 8:00

**Location**: Camp Dodge

**Contact: **tomschenkjr at gmail dot com

**Instructional Resources**

- Textbook: Understanding Statistics in Behavioral Sciences by Robert R. Pagano, 9th Edition, Wadsworth Publishing: 2008 ISBN-13: 978-0495596523
- Data: Census @ Schools, Data and Story Library, Classroom Survey of Basic Data,
- Blogs: See Statistical Modeling, Social Science Statistics, Observational Epidemiology
- Other materials will be distributed via the course website: www.tomschenkjr.net.

**Grading** –

All assignments will be scored on a 100 percent scale. The final grade, *Y*, will be derived using the following formula:

Y = 0.33 * A + 0.33 * E + 0.33 * F

where,

F = Final

E = Exam

A = Average of assignments

*Final/Exam:*** **The final will explicitly be cumulative, although the emphasis will be slightly more on the latter third of the class.

*Assignments:* Assignments will be given throughout the semester through the course website. Assignments will vary in size from a few questions, to larger assignments that may resemble class projects.

**Final Course Score**

A = 90-100%

B = 80-89%

C = 70-79%

D = 60-69%

F = < 60%

**Reading List**

9 May: Review of the syllabus and introduction

Scientific Method

***Chp. 1 – Pagano

Basic Mathematical Concepts and Measurement Concepts

***Chp. 2 – Pagano

**KhanAcademy lecture on means (and notation)

11 May: Central Tendency and Variability (In-class Survey)

***Chp. 3 – Pagano

***Chp. 4 – Pagano

**Anatomy of a Standard Deviation

**KhanAcademy lecture on variance

**KhanAcademy lecture on standard deviation

16 May:** NOTE: CLASS WILL START AT 6:45p
**

Graphing

***The Basics of a Basic Graph, tomschenkjr.net

18 May: Normal and Standard Normal Curves (a.k.a. bell curve)

***Chp. 5 – Pagano

***KhanAcademy lecture on Normal Distribution Curve

23 May: Correlation

***Chp. 6 – Pagano

25 May: Linear Regression

***Chp. 7 – Pagano

***Right-to-Work Law, *Wikipedia.org*

*****Two major labor bills reappear at the Capitol, Jason Clayworth, *Des Moines Register Blog*, February 4, 2010.* *

30 May:** NO CLASS – MEMORIAL DAY**

1 Jun: Linear Regression / Multiple Regresson

***Chp. 7 – Pagano

**An Introduction to Regression, A. O. Sykes.

** Squared Error of a Regression Line via KhanAcademy

** Coefficient of Determination / R-Squared via KhanAcademy

* Proof: Regressions Minimize Error: Part 1, Part 2, Part 3, Part 4 via KhanAcademy

**Take Home Exam**

6 Jun**: **Random Sampling & Probability

***Chp. 8 – Pagano

8 Jun**: **Introduction to Hypothesis Testing Using the Sign Test

***Chp. 10 – Pagano

13 Jun: Z-tests

***Chp. 12 – Pagano

15 Jun: Student’s t-Test

***Chp. 13 – Pagano

***Chp. 14 – Pagano

22 Jun: Analysis of Variance (ANOVA)

27 Jun: Review

**29 Jun:** **Take Home Final Due July 4th
**

**Missed Exams and Assignments**

Assignments will be due at the beginning of class every Tuesday and tests will be given on the days denoted below. Late assignments will be penalized 40 percent. Students must notify the professor of an upcoming absence. Students will be allowed to make up exams **ONLY** when the professor received prior notification for the inability to complete the exams. In extreme cases where prior notification is impossible, the student must provide written documentation—not by the student—explaining the absence. Students who miss a test for an unexcused absence will receive a zero.

**Attendance**

Students will be expected to attend every class. Irregular attendance will be reflected in participation and company exercise scores. Those who already anticipate missing two or more classes are encouraged to enroll at another time.

**Academic Integrity**

Grand View University is dedicated to the development of the whole person and is committed to truth, excellence, and ethical values. Personal integrity and academic honesty in all aspects of the University experience are the responsibility of each faculty member, staff member, and student.

A student has an obligation to do work that is his or her own and reflects his or her learning and quest for academic knowledge. Dishonesty and cheating are not acceptable behaviors. Examples include helping others during exams, writing papers for others, falsifying data/records, copying other students’ work, taking work directly from the Internet or any printed source and claiming it as one’s own, and downloading/purchasing papers on-line. Students who cheat, could risk severe penalties, which may include failure of the assignment, failure of the course, or expulsion from the University.

“As a member of the Grand View University community, and in accordance with the mission of the University and its Lutheran identity, I agree to appreciate and respect the dignity and worth of each individual. I will honor and promote a community of open interaction, personal integrity, active and intellectual engagement, and academic honesty with students, faculty, and staff.”

**Accelerated Courses**

Grand View offers courses in accelerated or alternative delivery formats. They cover the same subject content and require the same or comparable assignments that are associated with a traditional fourteen week course.

**Accommodation**

Grand View University prohibits unlawful discrimination and encourages full participation by all students within the university community. When a student requires any instructional or other accommodation to optimize participation and/or performance in this course, it is the responsibility of the student to contact both the instructor and the Director of Academic Enrichment and Disability Coordinator and apply for any requested accommodation. The director is Dr. Kristine Owens and she can be reached at 515/263-2971.

**Class Attendance**

The Federal Government requires that students receiving financial aid attend classes. Students, who are identified by the instructor as not attending classes, will be reported to the Registrar’s Office. Students who fail to return to classes may lose all or a portion of their financial aid.

**Classroom Conduct**

Students should conduct themselves as responsible members of the University community respecting the rights of others. Any student behavior interfering with the professor’s ability to teach and/or the student’s ability to learn constitutes a violation of the Code of Student Conduct found in the Grand View Catalog. The professor may ask the student to leave the classroom and that student will be subject to disciplinary sanctions.

**University E-Mail Account**

It is essential that all students check their Grand View University e-mail account or set their account to forward to a preferred e-mail address.

Students may set-up an e-mail auto forward from the myView web site. Click on the “Manage and Update Personal Information” link and then select “set myView Mail Forwarding Address” under the “Links for You” section.

**Appeal of Final Undergraduate Course Grade or Faculty Member’s Final Academic Disciplinary Action**

Students who wish to appeal a final course grade or other academic disciplinary action of an instructor must complete at least section I.A. of the Academic Appeal Form on-line within fourteen calendar days after the published due date for the final grade submission of the academic term in which the issue of disagreement occurred. Visit site below to complete first part of the form. https://secure/grandview.edu/gradeappealform.html

This form must be submitted electronically to the Office of the Provost. Nursing Students appealing a grade in a nursing course must follow the Nursing Division procedures.

**Homework**

- Homework #1 – Email me your preferred email address.
- Homework #2 – Due
~~May 24 by 8:00pm~~May 23 by 5:45p via email. - Homework #3 – Due June 1 by 5:45pm via email. Answers
- Exam – Due June 11 by 11:59pm via email.
- Homework #4 – Due June 20 by 5:45pm via email. Answers
- Final – Due July 2 by 11:59pm via email.

Professor Schenk,

In question three of our homework, is “SIGMA xi-mean” equal to “(SIGMA xi)-mean” or is it equal to “SIGMA (xi-mean)”?

Similarly, should I be getting the same answer for B and C in question 3?

Thanks.

Jill-

Excellent question. Without the parenthesis means you want to subtract the mean for each x_i. With parenthesis means you do the sum within parenthesis, i.e., SIGMA xi^2 means x1^2 + x2^2 + … and SIGMA (xi)^2 means (x1 + x2 + …)^2.

Thus, B and C should not be the same answer.

Prof. Schenck,

I have a question about #6. (Suppose there are 10,000 donations next year, how many will have total donations that exceed $100? How many will be less than $10?)

Do you mean the dollar amount or the number of donations when you say ‘how many’? I have calculated the dollar amount but I’m not sure how I would calculate the number of donations. I did a direct proportion on the number of donations but it seems too simple of a solution.

Thanks

Jill

Jill-

I do mean “how many” as in the number of donations that exceed $100 and also the number of donations that are less than $10.

Rely on your z-score and the use of normsdist in Excel. That will give you the percentage and probability of each range.

Is there a computer lab open tomorrow evening at Grand View? If so, is anyone willing to meet me there to work on this together? My email is ek.conklin@gmail.com.

I am on a Mac that has enough memory to run Photoshop files but having trouble with this file exceeding the memory. I got through the first and second questions just fine then ran into trouble on exercise 3 and 4.

Elisa

The library is open until 8p. I tested this HW assignment on an older computer with little issue, if anyone else is having memory issues please let me know ASAP.

Professor Schenk, I am confused about what the coefficients and standard error mean. How you would begin to asses how much participation in the engineering program changed the scores?

Thanks,

Jill

You will want to conduct an hypothesis test on the engineering variable.

Professor Schenk,

On homework 4 question 1b, how would I determine H subset 0 in the z-test formula?

“To have an impact” is another way of saying the impact is not zero. Or, that the coefficient is statistically different from zero.

Prof. Schenck,

On question 3 of the final, does this study want the graduation rates of universities to be better than liberal arts colleges? Or, is it appropriate to make a hypothesis in which their graduation rates are equal?

Thanks

Jill VF

Professor Schenk,

Are you going to post the answers to #4 so we can see which ones we got incorrect before we make the same mistakes on the final?

Erin-

Yes, I’m in airports today and will post it by tomorrow afternoon.

Prof. Schenck,

On question 4 of the final, is the goal to run a regression or independent sample t-test in SPSS? When I run a regression, I receive an error message that says:

“String variables are not allowed on the list.”

This error message occurs when I try to use the column School_Type as an independent variable.

I thought that doing an independent samples t-test would allow me to denote a liberal arts college versus a university with numerical vallues instead of text. Is it appropriate to run an independent samples t-test? If so, how do you define groups?

thanks

Jill VF

Jill-

Since we’re looking at the relationship between multiple independent variables and one outcome (graduation %), a regression would be most appropriate.

Sir,

I am having issues with question #3. I am trying to use the SPSS to seperate the info for Lib Arts compared to Uni and it keeps coming up with an error about not being able to use a string value. Would you be able to point me in the right direction on what I am doing wrong.

Thank You,

Michael Dolsen

Michael-

Yes, SPSS is unable to handle strings (computer-speak for “letters”). That’s because this variable is a categorical field (university or liberal arts isn’t inherently numerical). Consider making this variable numeric (e.g., binary) and try that.

My stats tutor says it looks to her like we will need to know ANOVA. I told her it was mentioned in class, but wasn’t that the last thing that had to be removed from the syllabus when you realized you would be out of town this last week? She has tutored other stats students in previous terms . . . I’m just feeling a little stuck here.

No, ANOVA is definitely not needed on the final. I opt to skip ANOVA in favor of regression.

Since you are not on Blackboard, can we expect our corrected tests along with our final grades to be e-mailed to us individually?

Tests will be returned individually, the final grades will be through the MyView website.