IT 223 Data Analysis

Marco Chou

Office: CDM 657
Fall 2023-2024
Class number: 12720
Section number: 401
MW 1:30PM - 3:00PM
LEWIS 01510 Loop Campus


Application of statistical concepts and techniques to a variety of problems in IT areas and other disciplines, using a statistical package for simple data analysis. Course topics include descriptive statistics, elementary probability rules, sampling, distributions, confidence intervals, correlation, regression and hypothesis testing. PREREQUISITE(S): MAT 130 or placement

Learning Domain Description

This applies only to undergraduate students – and therefore may not apply to any student currently in this course. IT-403 Data Analysis and IT-223 are included in the Liberal Studies program as a course with credit in the Scientific Inquiry domain. Courses in the Scientific Inquiry domain are designed to provide students with an opportunity to learn the methods of modern science and its impact on the world around us. Courses are designed to help students develop a more complete perspective about science and the scientific process, including: an understanding of the major principles guiding modern scientific thought; a comprehension of the varying approaches and aspects of science; an appreciation of the connection among the sciences; the fundamental role of mathematics in practicing science; an awareness of the roles and limitations of theories and models in interpreting, understanding, and predicting natural phenomena; and a realization of how these theories and models change or are supplanted as our knowledge increases.

Learning Domain Outcomes

1. Students will understand the major principles guiding modern scientific thought. Students will demonstrate a mastery of the science content knowledge of their SID courses.

2. Students will know that science, technology, and math serve as mechanisms for inquiry into the nature of the universe. Students will: ?

a. identify questions that can be answered through scientific investigations;

b. design and conduct a scientific investigation to test a scientific hypothesis;

c. use appropriate tools and techniques together, analyze, and interpret data to support or refute a scientific hypothesis;

d. develop descriptions, explanations, predictions, and models using evidence;

e. describe relationships between evidence and explanations using critical and logical thinking;

f. recognize and analyze alternative explanations and predictions;

g. communicate scientific procedures and explanations;

h. use mathematics in all aspects of scientific inquiry.

3. Students will understand and appreciate the interrelationships among science, technology and math. Students will:

a. use technology and mathematics to identify a problem or design a solution to a problem;

b. give examples of how science and technology inform and influence each other.

4. Students will understand and appreciate the role of science in society and in their lives. Students will:

a. Provide examples of how science and technology impact our lives, and how social needs and concerns impact our development of technology and scientific investigation;

b. develop positive attitudes towards science, technology, and mathematics;

c. establish an ongoing experiential/service-learning interest in science, technology, and mathematics.

5. Students will understand the nature of science, technology, and mathematics. Students will:

a. provide examples of the abuse of science, including the representation of unfalsifiable claims as science and other forms of pseudoscience;

b. explain the strengths and limits of scientific inquiry;

c. explain the difference between evidence and inference, and the ?provisional nature of scientific explanations by providing examples of how our understanding of the workings of the world has changed in the past;

d. explain the difference between probability and certainty, and describe what is meant by uncertainty in the context of science, technology, and mathematics.

How Learning Outcomes Will Be Met

Statistics is a rigorous intellectual challenge that must be approached systematically with extreme attention to detail. The assumptions, and mathematical rigor used to make decisions on which formulas to apply and to build and evaluate models require a solid understanding of the underlying theory. To that end, students will be asked not merely to “get the answer”, but to always justify their answer(s). Students will be confronted with scenarios in which the “expected” formula or model turns out to be the “wrong tool for the job”, and it is expected that they will be able to recognize such situations when they occur. In other words, the student will, at all times, be expected to understand the underlying theory and assumptions that underlie a given approach.

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. Courses in the SI domain must include a writing component where that component takes on the form appropriate for that course (e.g., lab reports, technical reports, etc.)

How Writing Expectations Will Be Met

  1. the course of the quarter, students will be required at times to provide clearly written summaries explaining some of the theories and models expounded upon during the course. The student will also be required to explain their own reasoning accompanied by specific examples from their own solutions to problems, and from their interpretation of examples discussed during the course.



· OpenStax Statistics: The IT program committee has moved to an online textbook that does not have a required payment. The publishers of the text do request a contribution, which I would encourage all of you to make, but it is not required. The textbook can be found at:

· OpenIntro Statistics: An excellent book. For certain topics, has better explanations than  OpenStax.

· Humongous Book of Statistics Problems: You can find this book at It is very inexpensive. While this cannot be used as the course textbook, it would be a very helpful tool for you in this course. In spite of its title, the book is not huge or daunting. It is a book of straight-forward exercises with explanations. Doing lots of problems is the key to getting through the course, so I would strongly encourage you to buy and use this book.


Lab: 40%

Homework: 40%

Midterm & Final: 20%


MAT 130 or above or equivalent or Mathematics Diagnostic test placement into MAT 140 is the prerequisite for this class.

WK#7-2 Exploratory Data Analysis (EDA) WK#8-2 Multiple Regression WK#9-2 Google Data Studio

School policies:

Changes to Syllabus

This syllabus is subject to change as necessary during the quarter. If a change occurs, it will be thoroughly addressed during class, posted under Announcements in D2L and sent via email.

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. Students complete the evaluation online in CampusConnect.

Academic Integrity and Plagiarism

This course will be subject to the university's academic integrity policy. More information can be found at If you have any questions be sure to consult with your professor.

All students are expected to abide by the University's Academic Integrity Policy which prohibits cheating and other misconduct in student coursework. Publicly sharing or posting online any prior or current materials from this course (including exam questions or answers), is considered to be providing unauthorized assistance prohibited by the policy. Both students who share/post and students who access or use such materials are considered to be cheating under the Policy and will be subject to sanctions for violations of Academic Integrity.

Academic Policies

All students are required to manage their class schedules each term in accordance with the deadlines for enrolling and withdrawing as indicated in the University Academic Calendar. Information on enrollment, withdrawal, grading and incompletes can be found at

Students with Disabilities

Students who feel they may need an accommodation based on the impact of a disability should contact the instructor privately to discuss their specific needs. All discussions will remain confidential.
To ensure that you receive the most appropriate accommodation based on your needs, contact the instructor as early as possible in the quarter (preferably within the first week of class), and make sure that you have contacted the Center for Students with Disabilities (CSD) at:
Lewis Center 1420, 25 East Jackson Blvd.
Phone number: (312)362-8002
Fax: (312)362-6544
TTY: (773)325.7296