OpenStax Introductory Statistics, Illowsky and Dean, 2018
openstax.org/details/books/introductory-statistics

OpenIntro Statistics, Diez, Cetinkaya-Rundel, and Barr, 2019
www.biostat.jhsph.edu/~iruczins/teaching/books/2019.openintro.statistics.pdf

Grading Breakdown: Midterm: 15%, Final 25%, Projects 40%, Practice Quizzes 10%, Attendance 10%
Grading Scale: 94-100:A, 89-93:A-, 85-88:B+, 80-84:B, 75-79:B-, 70-74:C+, 65-69: C, 60-64: C-, 55-59: D+, 50-54: D, 0-49:F.

The official late penalty for submissions is 10% for each day that the submission is late.  Projects will have a three day grade period before they are counted late. Students that have extenuating circumstances, late penalties may be reduced if you talk to the professor, in person, by phone, or via Zoom. Although it is possible for the late penalties to be reduced, they cannot be totally eliminated.

Quizzes cannot be taken late.  The lowest two quiz scores will be dropped.

Students in the async section obtain credit for attendance by submitting study logs, which are due each Tuesday for the preceding week (Sunday to Saturday). Study logs summarize what you did to study for IT 223 during the preceding week. Although exactly what you submit is up to you, here are some suggestions: the number of hours you spent studying for the various parts of the class (e.g., watching lectures and studying class examples, working on tutorials, projects, and practice quizzes), what did you find interesting, hard, or confusing, what questions did you have? If you have questions for the instructor, emailme directly, in addition to putting these questions in the study log.

MAT 130 or another college algebra course or Mathematics Diagnostic Test Placement Exam

Class registration is not allowed after the first week of class.
Projects may not be submitted after the project's grade has been posted, except under rare circumstances.
Students should keep backup copies of all submitted assignments in the rare case that an assignment must be resubmitted.
Extra credit assignments are not given. To give them would be unfair to the other students in the class.
Practice quizzes are include the adjective "practice" because they can be taken up to three times with the highest score counting.  Questions from the practice quizzes may also appear on the midterm or final exams.
No assignments will be accepted after the Sunday following finals week.
An incomplete is hard to get in CDM. It is only allowed for a major illness (typically requiring hospitalization) or a death in the family. In any case documentation is required, and more than one half of the work must be completed for the course.
Students that have trouble submitting any project, email the completed project to me to prove that you completed it on time.
Students that must miss an exam must contact me in advance to reschedule the exam.
Students that miss an exam without first contacting me, that exam can only made up if the following two conditions are met: (1) a late penalty is charged for the exam, (2) the student has a valid reason for missing the exam, with appropriate documentation,
Submitting a wrong version of a project is not a reason to waive a late penalty for that project.
Students that use a name that is different than the name on the roster or have preferred pronouns should let me know.

Online Course Evaluations
Evaluations are a way for students to provide valuable feedback regarding their instructor and the course. Detailed feedback will enable the instructor to continuously tailor teaching methods and course content to meet the learning goals of the course and the academic needs of the students. They are a requirement of the course and are key to continue to provide you with the highest quality of teaching. The evaluations are anonymous; the instructor and administration do not track who entered what responses. A program is used to check if the student completed the evaluations, but the evaluation is completely separate from the student’s identity. Since 100% participation is our goal, students are sent periodic reminders over three weeks. Students do not receive reminders once they complete the evaluation.

Academic Integrity and Plagiarism
This course will be subject to the university's academic integrity policy. The DePaul Student Handbook defines plagiarism as follows: “Plagiarism includes but is not limited to the following: (a) The direct copying of any source, such as written and verbal material, computer files, audio disks, video programs or musical scores, whether published or unpublished, in whole or in part, without proper acknowledgement that it is someone else’s. (b) Copying of any source in whole or in part with only minor changes in wording or syntax even with acknowledgement. (c) Submitting as one's own work a report, examination paper, computer file, lab report or other assignment which has been prepared by someone else. This includes research papers purchased from any other person or agency. (d) The paraphrasing of another's work or ideas without proper acknowledgement.” Plagiarism will result in a failure of the assignment or possibly of the course. If you are unsure of how to cite a source, ask!
More information can be found at http://academicintegrity.depaul.edu/. If you have any questions, consult with instructor.

Students with Disabilities
Students that need accomodations because of a disability should register with the Center for Students with Disabilities (CSD). Contact CSD at csd@depaul.edu
They should also contact me privately to discuss their specific needs. All discussions will remain confidential.

Learning Outcomes

1. Recognize and explain statistically based results from real data (either primary or secondary) and evaluate whether reported conclusions reasonably follow from the study and analysis conducted.
2. Use statistical software to produce and interpret graphical displays and statistical summaries.
3. Recognize and explain the roles of variability and randomness in interpreting data and drawing conclusions.
4. Explain common ethical issues associated with sound statistical practice, including those associated with research design, and their impact on statistical decision-making.
5. Measure the strength of association between variables and identify possible effects of confounding or interacting variables on the interpretation of the association.
6. Apply basic ideas of statistical inference, including confidence intervals or hypothesis testing, in a variety of settings.

Writing Expectations

Writing is integral for communicating ideas and progress in science, mathematics and technology. The form of writing in these disciplines is different from most other fields and includes, for example, mathematical equations, computer code, figures and graphs, lab reports and journals.

Throughout the course, students will be required to provide clearly written analyses of their interpretations of the results of their statistical calculations. The student will be required to explain their reasoning accompanied by specific examples from their own solutions to problems, and from their interpretation of concepts and examples discussed during the course.