Instructor | W. Joel Schneider |
---|---|

Office | DeGarmo 456 |

Phone | (309) 438‒8410 |

wjschne@ilstu.edu | |

Office Hours | Mondays 2–3pm Tuesdays 12noon–1pm and by appointment |

Tim Deering Office Hours |
Thursdays 1pm–1:50pm in the Psychology Resource Center in DeGarmo 17(next to the lab classroom) |

Jordan Thomas Office Hours |
Thursdays 2pm–2:50pm in the Psychology Resource Center in DeGarmo 17 (next to the lab classroom) |

Students develop skills both in statistical reasoning and statistical
method by actively engaging in the practice of statistics as science.
Students will study important current, psychological issues whose
understanding requires a fundamental knowledge of statistical concepts, in
particular, hypothesis testing and regression. Controversial topics will be
chosen that are currently in the news and likely to remain so. Such
psychological controversies are regularly found in journals and magazines
such as *American Psychologist* and *Current Directions in
Psychological Science*.

*Reasoning in Psychology Using Statistics* uses a
classroom/laboratory approach for analysis of data, for hands-on production
of data, and for simulation-based learning. According to Cobb (1993, p.4),
“the lab approach accords with the movement of statistics back towards its
roots in science, and with research in education that demonstrates the
importance of active learning.” Additionally, the classroom/lab setting
allows students to access the vast array of data available through the
Internet.

*Reasoning in Psychology Using Statistics* follows the guidelines
developed by the American Statistical Association (ASA) and the
Mathematical Association of America (MAA) which suggest that teachers
should:

- Motivate students by showing them statistics at work in real applications, problems, cases, and projects.
- Use real data and statistical computing (SPSS).
- Foster active learning

Almost any introductory social science statistics textbook will be helpful. The reason I no longer require a textbook is that there are so many free statistics resources on the web. A quick search on the search engine of your choice will probably bring new ones every day.

I recommend David Kenny’s free textbook

Here is another free statistics textbook.

Here is another.

*SPSS* - this software is
available on the classroom computers and on most other
campus lab computers. You do NOT have to purchase it for the class.
However, if you want a copy for your home computer, student versions are
available at the student bookstores. An open source and alternative to SPSS
is PSPP. You can analyze
SPSS datasets with PSPP.

I will also use Microsoft Word and Microsoft Excel often and will sometimes give you Excel tools for statistics. If you do not have Microsoft Office, OpenOffice.org offers a FREE, high-quality office suite that is compatible with Microsoft Office. Although OpenOffice uses a different format by default, you can save documents and spreadsheets in OpenOffice in the same format that Microsoft Office users use.

How to obtain and register the TurningPoint Response Card. I explain how I use these in class in the "Attendance" section below.

I have not used a hand calculator in years (I use Excel for everything.). However, most students will probably want to use a calculator for the course. Any reasonable calculator with a memory button will work. You are not permitted to use your cell phone’s calculator on exams.

A set of lecture notes in skeletal form will be posted on this course's ReggieNet site. They will be updated frequently, sometimes shortly before the lecture. These notes are posted for your convenience to reduce the burden of copying figures and text from my slides. However, failing to take notes of your own is a mistake. Notetaking facilitates learning because you have to understand a topic to summarize it.

Lecture and lab attendance is not optional. You are expected to attend every lecture and participate through discussion and classwork. All labs are in Room 13 in DeGarmo. Think of the labs as scheduled homework time with a tutor (your GA).

In lectures, from time to time, I will ask questions using the "Clicker" technology. You must give all your answers in good faith (i.e., no random or deliberately misleading responses). I will sometimes use your responses as data to illustrate data analysis. If the questions are about opinions or life history involving personal matters you will always have the option of clicking “I prefer not to answer this question.” I will never look at any individual’s response to these kinds of questions nor will I penalize anyone for choosing not to answer them.

Your class participation grade will be determined by the percentage of times that you participated using the Clickers. I will allow 2 unexcused absences before it affects the participation grade. You may make up classwork only if you were absent due to University sanctioned events, documented illnesses, or documented crises. Make-up assignments will typically be short essays.

If you forget your Clicker but you attended, you must do 2 things:

- Tell me you forgot your Clicker after class.
- Email me later telling me that you were in class.

Why do you need to tell me twice? Telling me in class makes it easy for me to believe that you were really there. Telling me by email makes it easy for me to give you credit.

Do not use an absent classmate’s Clicker to make it seem that the student was in attendance. This is dishonest and will result in an automatic failing grade for everyone involved in the activity.

Special circumstances may result in reasonable substitutes for missed assignments.

I reserve the right to change this syllabus as needed throughout the semester. I hope that these changes are few and minor. I will notify you of any changes that I make.

The work necessary to obtain the grade you desire has been outlined here. No additional work will be accepted to increase your grade. Do not come to me at semester’s end asking if there is some additional work you can do to increase your grade. At semester’s end, there is none.

Please visit me during my office hours with any questions you have. My job is to help you learn. If you need help, get it early; don’t wait until you find yourself saying “I’m so lost I don’t know what to ask!” If you cannot make it to my regular office hours then, please, make an appointment with me. Talk to me after class, call me at (309) 438‒8410, or e-mail me at wjschne@ilstu.edu.

Any student needing to arrange a reasonable accommodation for a documented disability should contact Student Access & Accommodation Services at 350 Fell Hall, (309) 438‒5853 (voice), (309) 438‒8620 (TTY).

Your grade will be determined by weighting your performance on the following:

**Class Participation:**Attendance in lecture will be taken by Clickers.**Labs:**Labs will include both group and individual exercises. Each of the labs will be described in a web page. Most of them will involve submitting answers to your GA by email and/or ReggieNet**Homework:**Problems to be worked on independently and submitted by ReggieNet.**Exams:**There will be three exams. They are cumulative to the extent that the material from later parts of the class build upon material from the early parts. These exams may include both conceptual and computational questions. The format will typically be both multiple choice and short answer. Some portions of the exams will be closed books. More information will be given in class.**Project**: You will demonstrate an integrative understanding of reasoning with statistics by analyzing a large dataset and writing up your results.

The grading scheme is not a curve. This is a good thing. This means that everyone can get an A if everyone performs well. Of course, this means that everyone could fail the course if everyone blows it off. A curve would make it so that only a certain percentage can receive high grades and that certain percentage would fail the course no matter how well they understand the material.

The percentage correct from each homework will be averaged to compute a total grade that is worth 100 points.

The percentage correct from each lab will be averaged to compute a total grade that is worth 100 points.

Assignment | Points |
---|---|

Attendance | 100 |

Labs | 100 |

Homeworks | 100 |

Project | 100 |

Exam 1 | 200 |

Exam 2 | 200 |

Exam 3 | 200 |

Total Points = 2 * Exam 1 + 2 * Exam 2 + 2 * Exam 3 + Average Lab + Average Homework + Project + Class Participation

Therefore, there is a total of 1000 possible points. Your final semester grade is determined as follows:

Performance | Grade |
---|---|

900–1000 | A |

800–899 | B |

700–799 | C |

600–699 | D |

0–599 | F |

You can use this Grade Calculator to estimate your grade this class.

Dates | Tentative topic calendar | Things due |
---|---|---|

8/22 | Introduction and syllabus review | Lab 1 |

8/24 | Variables | Lab 2 |

8/29 | Measurement | Lab 3 |

8/31 | Frequency Distributions | Lab 4 |

9/7 | Measures of Central Tendency | Lab 5 |

9/12 | Variability | Lab 6 |

9/14 | Normal Distribution | Lab 7 |

9/19 | Correlation | Lab 8 |

9/21 | Regression |
Lab 9 Homework 1 (Due at 11:55pm) |

9/26 | Review for Exam 1 (Study Guide) | Homework 2 (Due at 11:55pm) Practice Computational Exam (Required but not graded) |

9/28 | Exam 1 (Conceptual part in lecture, computational part in lab) | Link to Spreadsheet Tools |

10/3 | Sampling Distributions | Lab 10 |

10/5 | Null and Alternative Hypothesis Testing | Lab 11 |

10/10 | Hypothesis Testing | Lab 12 |

10/12 | Hypothesis Testing | Lab 13 |

10/17 | Statistical Power |
Lab 14 Homework 3 (Due at 11:55pm) |

10/19 | Confidence Intervals | Lab 15 |

10/24 | Review for Exam 2 (Study Guide) |
Lab 16 Homework 4 (Due at 11:55pm) |

10/26 | Exam 2 (Conceptual part in lecture, computational part in lab) | Link to Spreadsheet Tools |

10/31 | One-Sample t-test | Lab 17 |

11/2 | Paired samples t-test | Lab 18 |

11/7 | Independent samples t-tests | Lab 19 |

11/9 | Which test? | Lab 20 |

11/14 | Confidence Intervals with t-tests | Lab 21 |

11/16 | Regression and hypothesis testing | Lab 22 |

11/28 | Chi-Square | Lab 23 |

11/30 | Data Analysis in the Real World | Work on Project in Lab |

12/5 | Review for Computational/Lab Part of Exam 3 | Work on Project in Lab Homework 5 (Due at 11:55pm) |

12/7 | Review for Conceptual/Lecture Part of Exam 3 |
Project Due at 11:55pm Computational Part of Exam 3 (in lab during your scheduled lab times) Link to Spreadsheet Tools |

TBA | Conceptual Portion of Exam 3 in Edwards Hall 235 (same room as the lecture) |