IT 223: Data Analysis
Catalog Description
Introduction to univariate data analysis methods. Descriptive statistics and data visualization methods. Overview of sampling techniques for data collection, and introduction to statistical inference methods for decision making including simple linear regression, estimation procedures using confidence intervals and hypothesis testing.
Goals
A broad understanding of descriptive and inferential statistics is the primary goal of this course. In addition, students are expected to develop and practice the following skills:
- Developing and critiquing tests involving the interpretation and comparison of collected data
- Interpreting and presenting empirical results
- Applying statistical software
- Knowing when to consult an expert
The use of R will be taught in class.
Math and Computing Domain: Statistical Reasoning (MC-SR)
Students who successfully complete IT 223, will have fulfilled the Liberal Studies Program – Math and Computing Domain – Statistical Reasoning category requirement.
List of MC-SR Learning Outcomes
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 regarding which formulas to apply, as well as 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.
- 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.
- Use statistical software to produce and interpret graphical displays and statistical summaries.
- Recognize and explain the roles of variability and randomness in interpreting data and drawing conclusions.
- Explain common ethical issues associated with sound statistical practice, including those associated with research design, and their impact on statistical decision-making.
- Measure the strength of association between variables and identify possible effects of confounding or interacting variables on the interpretation of the association.
- Apply basic ideas of statistical inference, including confidence intervals or hypothesis testing, in a variety of settings.
Math and Computing Domain 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.
- Students will demonstrate skills in writing at an appropriate level of detail (including the ability to summarize effectively), choosing an effective format, paraphrasing and citation of sources as required, technical accuracy, and quality of expression, including grammar, spelling and word usage.
- Students will be required to write the equivalent of a minimum of five to ten pages, distributed across a series of assignments. Specific types of writing required will be a part of the description of assignments appropriate to the topics covered.