COURSE NUMBER: STAT 300
COURSE TITLE: Introduction to Statistics
NAME OF INSTRUCTOR: Dr Robert MacDonald
CREDIT WEIGHT AND WEEKLY TIME DISTRIBUTION: credits 3 (hrs lect 3 - hrs sem 0 - hrs lab 1.5)
COURSE DESCRIPTION: An introduction to the use of statistical methods. Descriptive statistics, frequency distributions, regression and correlation, inference on means and proportions, sampling distributions, analysis of variance, hypothesis testing.

Prerequisites: Mathematics 30-2 or the successful passing of an algebra competency test.
REQUIRED TEXTS: The Basic Practice of Statistics, 6th edition David S. Moore, William I. Notz, Michael A. Fligner Published by W.H. Freeman 2013
MARK DISTRIBUTION IN PERCENT:
 Written Assignments 20% Lab 20% Lab Exam 10% Midterm Exam 20% Final Exam 30% 100%
COURSE OBJECTIVES:When you are finished this course, you will:
• understand the role of variability in interpreting data.
• understand what “statistics” is.
• understand the role of statistics in scientific and other research.
• know how to spot the advantages and drawbacks of different ways of viewing and describing data.
• understand how probability is used in statistics.
• understand how to use measurement uncertainties.
• be able to interpret the results of statistical analyses and draw conclusions.
The goals of the laboratory component are:
• to enhance your understanding of the concepts covered in class, through experience conducting statistical analyses.
• to introduce you to computer-based statistical analysis.
COURSE OUTLINE:
• January
• Chapters 1 & 2 Introduction; exploring data graphically & numerically
• Chapter 3 Normal distributions
• Chapters 8 & 9 Sampling, surveys, & experimental design
• Chapters 10 & 11 Probability & sampling distributions
• February
• Chapters 14–16 Introduction to confidence intervals & hypothesis tests
• Chapters 18 & 19 1-sample & 2-sample inference using t-distributions
• March
• Chapters 20 & 21 1-sample & 2-sample inference about proportions
• Chapter 25 ANOVA
• Chapter 4 Describing relationships graphically & numerically
• Chapter 5 Linear regression; association vs causation
• April
• Chapter 6 Two-way tables

Required texts, assignments, and grade distributions may vary from one offering of this course to the next. Please consult the course instructor for up to date details.

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