MATH 153A Statistical Reasoning
This algebra-based probability and statistics survey course covers basic descriptive statistics, binomial and normal distributions, confidence intervals, and hypothesis testing using z, t, chi square, and f distributions. The course also has a basic introduction to correlation and regression. Students are encouraged to complete the CSI Math Self Placement prior to registering for this course.
Corequisite
Math 152
General Education Competency
Mathematical Way of Knowing
Notes
For appropriate math placement, all students should complete the
CSI self-placement process provided by the Mathematics Department before signing up for their first math course.
MATH 153AStatistical Reasoning
Please note: This is not a course syllabus. A course syllabus is unique to a particular section of a course by instructor. This curriculum guide provides general information about a course.
I. General Information
II. Course Specification
Course Type
{5B2306C7-58E4-43D4-B8A5-26C59F89A734}
General Education Competency
Mathematical Way of Knowing
Credit Hours Narrative
3 Credits
Semester Contact Hours Lecture
45
Semester Contact Hours Lab
0
Corequisite Narrative
Math 152
Notes and Advisories (only if included in catalog)
For appropriate math placement, all students should complete the
CSI self-placement process provided by the Mathematics Department before signing up for their first math course.
III. Catalog Course Description
This algebra-based probability and statistics survey course covers basic descriptive statistics, binomial and normal distributions, confidence intervals, and hypothesis testing using z, t, chi square, and f distributions. The course also has a basic introduction to correlation and regression. Students are encouraged to complete the CSI Math Self Placement prior to registering for this course.
IV. Student Learning Outcomes
Upon completion of this course, a student will be able to:
- Create a graph and numerical summaries of a data set and provide a brief, written summary of the data.
- Explain components of well-designed observational studies and experiments.
- Given a scatterplot, describe the relationship between two variables.
- Identify when the normal model is appropriate and use the model to assign probabilities to events.
- Construct and interpret an interval estimate of a population parameter.
- Perform and interpret a hypothesis test for a population parameter.
V. Topical Outline (Course Content)
VI. Delivery Methodologies
Specific Course Activity Assignment or Assessment Requirements
The course will cover the following topics: descriptive statistics, data collection, probability, introduction to inference (hypothesis testing and confidence intervals), regression and correlation.
Student Project: Read and interpret a journal abstract or explain published results in a scientific study.
Final Exam: Departmental Comprehensive Final Exam that counts worth 20% or more of a student’s grade.