STAT 300 Outline

THE KING'S UNIVERSITY

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.