# Stats Prep: Intro to Basic Quantitative Methods

Stats Prep: Intro to Basic Quantitative Methods is a non-credit course that prepares students who are required to take University of Windsor’s SOSC 2500 Basic Quantitative Methods in the Social Sciences class (or other similar).

The virtual instruction teaches core concepts of basic quantitative methods, and helps students understand key mathematical concepts, complete practice questions, and build their confidence. This course should be taken one or two semesters before enrolling in SOSC 2500 Basic Quantitative Methods credit class.

In a four-week series, students will be introduced to descriptive and inferential techniques used in quantitative social research. Topics include graphing basics, counting principles, probability, normal distribution, Poisson distribution, Binomial distribution, geometric distribution, confidence intervals and hypothesis testing.

No math background is required.

This class is specifically designed as a prep course for students in the Faculty of Arts, Humanities and Social Sciences who are required to take SOSC-2500 Basic Quantitative Methods in the Social Sciences. Students who are required to take similar Quantitative Studies classes in other faculties may also benefit from this course and are welcome to register.

### Course Outline

During class, learners will attend live online lectures, complete practice quizzes, complete homework questions and be provided with time to ask questions. The classes will focus on learning and there will be no tests or assessments.

### Learner Outcomes

Upon successful completion of the course, learners will:

• Plot and interpret different graphs such as stem-and-leaf, scatter plot, histograms, dot plots etc.
• Calculate measures of central tendency and measures of dispersion.
• Understand and apply counting principles to calculate probabilities of random events.
• Calculate mean, variance and standard deviation given a probability distribution.
• Read probabilities and quantiles from Z and t-tables.
• Explain the importance and features of a normal curve.
• Standardize normal data given population parameters.
• Build and interpret confidence intervals.
• Test null hypotheses with Z and t ratios.
• Recognize the difference between one-tailed and two tailed scenarios.

"Rong Luo is a fantastic teacher who is determined to help students understand the material and asks students if they have any questions in each lecture"
- Brooklyn L.

"This course was a nice intro to prepare for what is expected in the actual class. The instructor gave examples and alowed us to ask questions."
- Laurel R.

### Course Details

Format: Online Classroom

Fees: \$169 + HST. UWindsor students, staff and alumni are eligible for a discount. Email continue@uwindsor.ca for details.

Participants will need a scientific calculator for the class.

No textbook is required.  Open-source materials will be used.  Course materials will be provided through Brightspace.

### Prerequisites

• Experience working with word processing, email and web browsing
• English language proficiency
• Successful completion of a Secondary School Diploma

No math background required.  Verification may be requested.

Rong Luo, PhD

Dr. Rong Luo, PhD in statistics, serves as a Learning Specialist and Statistical Consultant at the Academic Data, Leddy Library, University of Windsor. In her role, she is dedicated to offering expert statistical advice and software support (R, SAS, STATA, SPSS) to the University's community members.

Technical Requirements:

• Learners will require access to a computer with high-speed internet access.
• Class is delivered online through the Brightspace Learning Management System (for class materials and assignments) and Microsoft Teams for class meetings.

Brightspace and Microsoft Teams Requirements

• A link will be provided through email prior to the first day of class so that you will have access to all course resources and streaming functions
• Once you register for this class you will be issued a UWinID. Please activate your UWinID as soon as possible. Document your UWinID and password as you will need it to access Brightspace and Teams. If you have any issues, please contact continue@uwindsor.ca.
• Visit this site for Brightspace technical requirements