MATH 291 Resource Statistics II is a continuation of Math 190 Resource Statistics I. Topics include linear regressions and correlation, inferential statistics, confidence intervals, hypothesis testing, goodness of fit, contingency tables, and ANOVA.
Prerequisites: MATH 190 with a minimum grade of 60%
Accessibility Services Notice
Students who would like an academic accommodation and who have a documented disability should contact Accessibility Services, if they have not already done so.Course Details| Total number of weeks | 15 |
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| Total Credits | |
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| Total Hours | 30 |
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Typical hours per week breakdown| Lecture | 2 |
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Learning Outcomes
Upon successful completion of this course, the learner will be able to:
- Interpret, organize, display, and describe data
- Formulate research questions and hypotheses
- Apply a variety of basic statistical tests and techniques to real-world data
- Interpret the results of statistical tests
- Define and utilize statistical terms and language
Teaching and Learning Approach
Class meetings are interactive with students analyzing data sets, formulating research questions, and
interpreting statistical results. Weekly independent work completed outside of class meetings includes reviewing
mathematical skills essential for analyzing data sets. Assessments and class meetings require the use Microsoft
Excel. Students are responsible for checking the course Moodle site for assignments, data sets, course updates,
and auxiliary learning materials.Learning Resources
Required:
- Illowsky & Dean. 2022. Introductory Statistics. BCcampus OpenEd and OpenStax.
- Microsoft ExcelDetailed Course Content, Topics, and Sequence Covered
1. Types of Data, Descriptive Statistics, Data Visualization, Confidence Intervals (numerical and categorical data)
2. One Sample Hypothesis Tests: numerical and categorical data, one-tailed and two- tailed.
3. Two Sample Hypothesis Tests: numerical and categorical data, one-tailed and two- tailed.
4. Midterm Exam: written during scheduled class time
5. Correlation and multiple linear regression
6. One-way ANOVA
7. Review
8. Cumulative Final ExamAssessment
| Title | Learning Outcomes | Value |
|---|
| Labs (5, collaborative) | 1 through 5 | 40% |
| Quizzes (10, independent) | 1 through 5 | 20% |
| Midterm Exam | 1 through 5 | 15% |
| Final Exam (cumulative) | 1 through 5 | 25% |
| Total | 100% |
Grading Table
Standard Academic and Career Programs Grading Table
| Percentage |
Letter Grade |
GPA |
| 90-100 |
A+ |
4.33 |
| 85-89 |
A |
4.00 |
| 80-84 |
A- |
3.67 |
| 76-79 |
B+ |
3.33 |
| 72-75 |
B |
3.00 |
| 68-71 |
B- |
2.67 |
| 64-67 |
C+ |
2.33 |
| 60-63 |
C |
2.00 |
| 55-59 |
C- |
1.67 |
| 50-54 |
P |
1.00 |
| 0-49 |
F |
0.00 |
| |
DNW |
0.00 |
See the Academic Calendar for General Information including how to withdraw from course(s) and other regulations.
Disclaimer
Information contained in this course outline is correct at the time of publication. Content of the course is revised on an ongoing basis to ensure relevance to changing educational, employment and market needs. The instructor will endeavor to provide notice of changes to students as soon as possible. The instructor reserves the right to add or delete material from courses.