Instructor: | W. Joel Schneider |
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Office: | DeGarmo 456 |

Phone: | 438-8410 |

e-mail: | wjschne@ilstu.edu |

Office hours: | Mondays & Wednesdays 11am–noon, and by appointment |

Semester: | Spring 2016 |

Times: | MW 12:35–1:50pm |

- Develop a thorough understanding of regression analysis
- Master basic techniques of reproducible research
- Conduct basic and advanced regression analyses in R and in SPSS
- Create publication-ready graphics that succinctly communicate findings
- Communicate results and their interpretation in APA style

Keith, T. Z. (2015). *Multiple regression and beyond* (2nd ed.). New York: Routledge.

Fox, J. (2016). *Applied regression analysis & generalized linear models* (3rd ed.). Thousand Oaks, CA: Sage.

Fox, J. & Weisberg, S. (2011). *An R companion to applied regression* (2nd ed.). Thousand Oaks, CA: Sage.

- R (current version)
- RStudio (Desktop, Open Source Edition) or (Preview Version)
- SPSS (available in all campus labs)

- You are expected to attend every lecture prepared to discuss assigned readings.
- You are expected to participate in all in-class assignments and exercises.
- You are expected to bring a laptop computer to class capable of connecting to the internet and running RStudio.
- If you are unable to attend a lecture, you are expected to meet with me to discuss a plan to make up what you missed.
- Excessive absences may result in a failure to complete the course. More than 2 absences is excessive.

- A series of homework assignments will be made available throughout the semester.
- Most assignments will be completed using R Markdown, such that the instructor will be able to run your markdown document and obtain the correct answers.
- Grades for most assignments will be based on
- Accuracy (80%)
- Readability & Grammar (10%)
- Aesthetic quality (10%).

The midterm and final exams will involve a closed-notes portion in which no computer will be allowed and an open-notes portion in which a computer will be required.

All pass/fail assignments must be passed to receive a grade in the course. With instructor permission, failed assignments may be attempted a second time.

Homework Exercises | 400 points |
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Midterm Exam | 300 points |

Final Exam | 300 points |

Total | 1000 points |

Grades are assigned in the traditional manner.

Performance | Grade |
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900-1000 | A |

800-899 | B |

700-799 | C |

600-699 | D |

0-599 | F |

If you need a special accommodation to fully participate in this class, please contact Disability Concerns at 438-5853 (voice), 438-8620 (TDD).

Plagiarizing and cheating on exams and other assignments are not tolerated. Any student exhibiting academic dishonesty will receive an F in the course and will be referred for disciplinary action. Disciplinary action may include expulsion from the university.

The best way to reach me is by email or in person, before or after class. I do not check my office telephone messages nearly as often as I check my email. I may, from time to time, email you about various matters.

- Work is due at the beginning of class on the date noted in the syllabus.
- Late work will only be accepted if approved by the instructor, and then at a 10% penalty per day.
- I reserve the right to change the syllabus as needed. You will be notified of all changes to this syllabus.