# Presentation of Statistics (MAT2246.01)

Josef Mundt

Data can come to us in many forms: tables, charts, graphs, observations, experimental results, and other less formal avenues. To best understand the world around us, we must be able to take that data, answer questions, and then convey those answers to others in a clear, concise manner. This course will show different methods for presenting statistical data to others as well as interpreting the information and results accordingly.

This course will serve as an introduction to statistical reasoning and understanding as well as bolster the ability to think critically about data, its sources, and how to convey a clear message from data. It will focus on bringing clarity to data presented, choosing the correct presentation for a given data set, and avoidance of deception. There are no prerequisites and this course will be accessible to all interested and willing students.

This course is appropriate for any students wanting to understand, interpret, and present statistics. Students who plan to seriously create and analyze their own statistics for their work should take Creation of Statistics, which may either be taken as a sequel to this course, or on its own. There is some overlap between the two courses, but their focus and goals are different. Students who take Presentation of Statistics first will get a broader skill set and a more gentle introduction.

Learning Outcomes:
- Assess the validity of the experimental or sampling design and statistical analysis of others.
- Identify misunderstandings about statistical reasoning and critique (mis)applications of data.
- Properly critique a graphical representation and offer constructive criticism in order to clarify the goal.
- Explain statistical ideas that underlie the central limit theorem, and use them to make statistically sound assessments of data.
- Assess color, style, and functions of graphs to balance readability and usefulness of graphical representations.
- Identify the appropriate plot and type of analysis needed to answer a given research question and explain the output contextually.
- Explain the results of hypothesis testing and confidence intervals in laymanâ€™s terms.

Delivery Method: Fully in-person
Course Level: 2000-level
Credits: 4
T/Th 6:30PM-8:30PM (Full-term)
Maximum Enrollment: 20
Course Frequency: Once a year

Categories: 2000 , All courses , Four Credit , Fully In-Person , Mathematics
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