PREP 7108 - 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 live, online 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.
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.
- 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.
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 Blackboard Collaborate.
Instructional time will be held on Microsoft Teams. As a student of this course, the University of Windsor will provide you with access to Microsoft Teams if you do not already have access.
As a University of Windsor student you can use your UWinID and password to register for the course and access Microsoft Teams. If you have any issues, please contact firstname.lastname@example.org.
Microsoft Teams is available in three versions including desktop, web and mobile app. The Microsoft Teams desktop app is available for both Windows 7 and 10 and macOS 10.10 or later. On Windows, Teams requires .NET framework 4.5 or later; the Teams installer will offer to install it for you if you don't have it. If you are unable to install Desktop App, you can use web version of Teams. In addition, Microsoft Teams mobile app is available for iOS and Android devices. You can download it from your respective app store on the device. Full instructions will be provided before the course start.
course details can be accessed through Blackboard. A link will be provided through email and you will have access the first day of class.
As a UWindsor student you will need your UWinID and password to access Blackboard. If you have any issues, please contact email@example.com.
Blackboard.uwindsor.ca works best with Google Chrome. You can also use Firefox or Safari. It is suggested that you avoid using Internet Explorer. There is a “Navigating Your Online Course” module and technical tutorials that you can review for a brief orientation to Blackboard once you log in. Feel free to review the full Blackboard preferred system requirements.
Minimum admission requirements include:
- 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.