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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)STAT*2060STAT*2080STAT*2120STAT*2230. This is a Priority Access Course. Enrollment may be restricted to particular programs or specializations. See department for more information.  Open Learning program students, please contact the Open Learning program Counsellor at Counsellor@OpenEd.uoguelph.ca.

 

 

Assessment

Assessment Item Weight
Term Test 1 15%
Term Test 2 15%
Term Test 3 15%
Data Analysis Assignment 1 12.5%
Data Analysis Assignment 2 12.5%
Online Final Exam 30%
Total 100%

 

Technical Requirements

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*Course details are subject to change.

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