SYLLABUS
MATH 115 - INTRODUCTION TO STATISTICS
(Traditional Format)
CATALOG DESCRIPTION: Description of data, binomial and normal
distributions, estimation and testing hypotheses for means and proportions.
Prerequisites: Two years high school algebra, one year of geometry and a
satisfactory placement exam score.
GENERAL DESCRIPTION: The main
objective of MATH 115 is to give the non-mathematical student an elementary
introduction to the practice of statistics. This course will give insight into
how a statistician gathers, summarizes, and draws conclusions from data. We are
surrounded everyday by numerical information and graphical material. At the end
of the course, the student should be a critical consumer of this information.
TEXT:
Moore, David S. The Basic Practice of Statistics, 4th Edition
CALCULATOR: The purchase of a TI-83
Plus or TI-84 Plus calculator is required or highly recommended.
CONTENT:
PART I:
EXPLORING DATA
Exploring
Data: Variables and Distributions
|
Chapter 1.
Picturing Distributions with Graphs Chapter 2.
Describing Distributions with Numbers Chapter 3. The
Normal Distributions |
You can
cover all the graphs and descriptive statistics discussed in Chapters 1 and
2. It may seem
odd to cover normal curves before we talk about probability. At this point, we think of the normal
curve as a data distribution.
Area under the curve corresponds to proportions of data that fall in
different intervals. |
Exploring Data: Relationships
|
Chapter 4.
Scatterplots and Correlation Chapter 5.
Regression Chapter 6.
Two-Way Tables |
Note that we really don’t focus on the computation of a
correlation and a regression line – rather, the interpretation of these
quantities is the most important. Important idea is to use conditional distributions to describe
association in a two-way table.
Don’t have to discuss Simpson’s paradox. |
PART II: FROM EXPLORATION TO INFERENCE
Producing
Data
|
Chapter 8.
Producing Data: Sampling |
Focus mainly
on the simple random sample (SRS) and the randomized comparative experiment. |
Probability and Sampling Distributions
|
Chapter 10.
Introducing Probability |
The
probability chapter is pretty brief and can be covered quickly. The notion of
a sampling distribution is a difficult concept and I would cover carefully. |
Introducing Inference
|
Chapter 14.
Confidence Intervals: The Basics |
These chapters
explain the fundamental concepts behind estimation and testing. |
PART III:
INFERENCE ABOUT VARIABLES (OPTIONAL)
|
Quantitative
Response Variable Chapter 20.
Inference About a Population Proportion |
You may not
have time to get to these sections.
Here you are applying what was learned in Chapters 14 and 15 to
learning about a population mean and a population proportion. |
SUGGESTED
TIMETABLE (MOORE) FOR COVERAGE THROUGH CHAPTER 16
|
WEEKS |
CHAPTERS |
|
1 |
Ch 1 –
Picturing Distributions with Graphs |
|
2 |
Ch 2 –
Describing Distributions with Numbers |
|
3 |
Ch 3 –
The Normal Distribution |
|
4 |
Ch 4 –
Scatterplots and Correlation |
|
5 |
Ch 5 –
Regression |
|
6 |
Review and
Test 1 |
|
7 |
Ch 6 –
Two-Way Tables |
|
8 |
Ch 8 –
Producing Data: Sampling |
|
9 |
Ch 9 –
Producing Data: Experiments |
|
10 |
Ch 10 –
Introducing Probability |
|
11 |
Review and
Test 2 |
|
12 |
Ch 11 –
Sampling Distributions |
|
13 |
Ch 14 –
Confidence Intervals: The Basics |
|
14 |
Ch 15 –
Tests of Significance: The
Basics |
|
15 |
Ch 16 –
Inference in Practice and Review |
|
Final Exams Week |
Test 3 |