### THE KING'S UNIVERSITY

COURSE NUMBER: SOCI 311
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.

Same as STAT 300

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.