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Course Description

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This course focuses on the practical methods of Statistics and the topics include: descriptive statistics; univariate models such as binomial, Poisson, uniform and normal; the central limit theorem; expected value; the t, F and chi-square models; point and interval estimation; hypothesis testing methods up to two-sample data; simple regression and correlation; introduction to analysis of variance. Assignments will deal with real data from the natural sciences and involve the use of statistical software for computing and visualization.

Learning Outcomes

By the end of the course, the learner should be able to:

  1. Create and properly interpret numerical and graphical data summaries;
  2. Properly interpret probability and carry out basic probability calculations;
  3. Carry out probability calculations for various discrete and continuous probability distributions, and choose the appropriate probability distribution in different scenarios;
  4. Explain statistical inference concepts, including sampling distributions, confidence intervals, and hypothesis tests;
  5. Choose an appropriate statistical inference procedure in a variety of situations, carry out the procedure, and effectively communicate a proper interpretation of the results;
  6. Explain the design of some basic experiments and observational studies, and describe how statistical conclusions differ between experiments and observational studies; and
  7. Carry out calculations for statistical inference procedures using appropriate statistical computing software.

Course Topics

  • An Introduction to Statistics and Statistical Inference
  • Tables and Graphs for Summarizing Data
  • Numerical Summary Measures
  • Probability
  • Random Variables and Discrete Probability Distributions
  • Continuous Probability Distributions
  • Sampling Distributions
  • Confidence Intervals Based on a Single Sample
  • Hypothesis Tests Based on a Single Sample
  • Confidence Intervals and Hypothesis Tests Based on Two Samples or Treatments
  • The Analysis of Variance
  • Correlation and Linear Regression

Additional Requirements

Prerequisite(s): 1 of 4U Calculus and Vectors, Advanced Functions and Calculus, OAC Calculus, MATH*1080

Restriction(s): This is a Priority Access Course. Enrolment may be restricted to particular programs or specializations. See department for more information.

Assessment

Assessment Item Weight
Online Quiz 1 7%
Online Midterm Exam 20%
Online Quiz 2 7%
Assignment #1 12%
Assignment #2 12%
Assignment #3 12%
Online Final Exam 30%
Total 100%

 

Note:

Additional Technical Requirements

This course will use the following:

  • Crowdmark is an online testing and assessment software that is used in this course. Visit the Crowdmark website to review the Crowdmark system requirements

Please view the Technical Considerations.

Technical Requirements

You are responsible for ensuring that your computer system meets the necessary system requirements. Use the browser check tool to ensure your browser settings are compatible and up to date (results will be displayed in a new browser window).

*Course details are subject to change.

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Section Title
Statistics I
Type
Online
Dates
September 09, 2021 to December 03, 2021
Contact Hours
36.0
Delivery Options
Online  
Course Fee(s)
Domestic Tuition Fee (0.5 units) $683.39 Click here to get more information
International Tuition Fee (0.5 units) $2,908.38 Click here to get more information
Available for Credit
0.5 units
Section Notes

Note:  If you are in a degree program at the University of Guelph, please DO NOT register using the link above.  You must register through WebAdvisor.

Section Materials
  • Supplementary (Confirmed) (Mandatory) There is no text to purchase, and the materials are available under “Supplementary Materials” on the course site.
  • Supplementary (Confirmed) (Mandatory) Introductory Statistics Explained (PDF) by Jeremy Balka © 2015 1.10 edition
  • Supplementary (Confirmed) (Mandatory) Suggested Exercises and Answers for Introductory Statistics Explained (PDF)
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