SOCIOLOGY
3811- BASIC SOCIAL STATISTICS
Spring 2000, Tu Th
11-12:15 in 10 Blegen
Professor: Christopher Uggen Teaching Assistants:
(Pronounced
You-Gun) Kristin Carbone;
1123 SS; 4-0201
1160 Social Sciences: 624-4016 carb0011@tc.umn.edu
Office:
Tu 11-2 or by appt.
uggen@atlas.socsci.umn.edu huan0147@tc.umn.edu
Logic of
the Course
Sociology 3811 is a
social statistics course for undergraduate sociology majors. We emphasize
techniques for describing data
and testing hypotheses. In lecture, you will learn the theoretical basis of
these techniques and how and when to apply them in social research. In labs,
you will learn technical computing skills and will apply these skills to
problems and assignments. By the end of the course, you will gain a working
knowledge of basic descriptive statistics, cross-classification tables,
probability and estimation, analysis of variance, and regression analysis. Many
of the in-class examples will be drawn from the sociological literature on
crime, law, and deviance.
Course
Objectives
1. General Knowledge: Help you to become a better consumer of statistics.
2. Sociological Knowledge: Teach you about sociology by showing how it is done.
3. Technical Skills: Help you become a better user of statistics and computers.
4. Analytic Skills: Teach you to do quantitative sociological analysis.
5. Life skills: Learn to present and interpret statistical
information.
What You Need
TEXT: Healey, Joseph F. 1999. Statistics:
A Tool for Social Research, Fifth Edition.
Why I chose this book (or why you
should feel good about spending $70):
(1) Of all the introductory
statistics textbooks available, Healey's may be the most accessible to students -- the friendliest and easiest to
understand.
(2) Healey
introduces the statistical software SPSS.
This will get you started without requiring a costly reference
manual. Other texts are designed around
outdated, clumsy, or needlessly complicated statistics packages.
(3) Healey uses important current
data sets, such as the General Social Survey. Your exercises are "doing
sociology" rather than make-work problems with meaningless data.
(4) The text offers many practice
problems and answers to odd-numbered problems, a useful glossary, and
index. All will be excellent resources
as you prepare for exams.
Recommended
Texts and Resources
·
SPSS Base 9.0: A Brief Guide (Available at
Lecture
Labs Lab 2:
Lab
DISK: At least one 3.5” floppy disk for
your computer lab work
CALCULATOR: A cheap one is OK as long as it
has a square root key
Course
Policies, Expectations, and Friendly Reminders
1. GRADING.
·
2
in class examinations (25% each)
·
2
take home assignments (10% Each)
·
1
final project (30%)
2. LATE
ASSIGNMENTS, MAKE-UP EXAMS, AND INCOMPLETES.
·
ASSIGNMENTS: Assignments are due to lab instructors AT THE
BEGINNING OF CLASS on the date noted in the syllabus. Late assignments are
penalized at least 5% per day. If family
or medical emergencies prevent you from attending class, provide written
documentation of the emergency. In such cases, you may also fax your lab
instructor the assignment at (612) 624-7020.
·
MAKE-UP
EXAMS: Students who miss exams due to verifiable illnesses, family emergencies,
religious observances, or University-sponsored events may take make-up exams.
In our experience, grades on make-up exams have tended to be lower than grades
on scheduled exams. Take the scheduled exam if possible.
·
INCOMPLETES:
No incompletes will be given for this class.
·
SNOW:
Sometimes it snows in
3. RESPONSIBILITY. You are
responsible for everything discussed
in lecture and labs, including changes to assignments handed out in previous
sessions.
4. LOWDOWN DIRTY CHEATS. I trust
my students not to cheat. When this trust is violated, I am personally offended
and vigorously prosecute academic misconduct.
5. TEACHING PHILOSOPHY, COLLEGE,
AND DEPARTMENT POLICIES: ATTACHED.
Tentative Class Outline,
Exams, and Assignments
Week 1
1/18 1 Introduction and Welcome pp
508-16
·
Math
review pp 508-516 of Healey
·
Blocks
to learning statistics and levels of analysis
·
Pacing,
Pitching, and the Broom
·
Descriptive
and Inferential Statistics
1/20 2 Scales of Measurement and Levels of
Analysis ch
1-2
·
Nominal,
Ordinal, Interval, and Ratio scales of measurement
·
The
logic of scientific research/statistics in scientific research
·
Samples
and populations
·
Data
reduction- Introducing basic descriptive statistics
1/25 3 Frequency Distributions and Graphical Techniques ch 2
·
Percentages,
Proportions, Ratios, and Rates
·
Univariate (one variable) distributions
·
Standardizing
distributions to a common base
·
Pie
charts, Bar Charts, Histograms, Frequency Polygons
·
Creating
charts and graphs in word processors and spreadsheets
1/27 4 Measuring Central Tendency ch 3
·
The
typical or average case in the distribution
·
Mode,
Median, and Mean
·
Grouped
and ungrouped data
Week 3
2/1 5 Measuring Variation: The variety in the
distribution ch
4
·
IQV:
index of qualitative variation
·
R:
range and Q: interquartile range
·
s2: variance
·
s:
standard deviation
·
Application: Evaluating investment risk
·
NOTE:
this is usually where people begin to have trouble. Make sure you keep up with
the reading and attend lecture and labs.
2/3 6 Form:
The
·
Dispersion
and the
·
Standardization:
Z-scores
and deviation units
·
Finding
areas of the normal curve
·
Symmetry
and Kurtosis
Week 4
2/8 7 Probability Theory and the
·
Probability
and the
·
Probability
and Sampling
NOTE: Assignment #1 due at beginning of class
Thursday 2/10
2/10 8 Sampling
Theory & the Sampling Distribution 6.4-6.5
·
EPSEM
Sampling Techniques
·
Samples,
Populations, and Sampling Distributions
·
Advanced Topic: Sample Selection Bias
Week 5
2/15 9 Estimation 7.1-7.3
·
Estimator
Properties: Bias, Efficiency, Consistency
·
Methods
of Estimation
2/17 10 Interval Estimation 7.4-7.6
·
Means
and Proportions
·
Advanced Topic: Bounding estimates
Week 6
2/22 11 Summary and Review of Descriptive
Statistics and Estimation
2/24 12 Exam #1
Week 7
2/29 13 The Logic of
Hypothesis Testing 8.1-8.3
·
Healey’s
Heuristic
·
One-
and Two-tailed Tests
3/2 14 One
Sample Tests for Means and Proportions 8.4-8.7
·
Types
of Error
·
Student’s
t distribution
·
Midterm
Evaluations of Uggen and TAs
Week 8
3/7 15 Two Sample Tests 9.1-9.3
·
The
Two Sample t-test for Differences in Means
3/9 16 Two Sample Tests 9.4-9.6
·
Matched
Samples
3/14 17 Bivariate Association & Crosstabulation ch
13
·
Interpreting
Tables -- Common Conventions
·
Independent
(X)
and Dependent (Y) variables
·
Row
and column percentages
3/16 18 The Chi-Square Test for
·
Hand-Cranking
Chi-Square (c2) values
·
Chi-Square
as an Overall Fit Statistic
·
Testing
the Statistical Significance of a Bivariate Relation
Week 10
3/21 19 Quantifying Association-Nominal &
Ordinal Level ch
14-15
·
Using
c2: Phi and Cramer’s V
·
The
Logic of PRE: Proportional Reduction in Error
·
Interpreting
Lambda
l and Gamma (G) (Pp.
353-68)
NOTE: Assignment
#2 due at start of class on Thursday
3/23 20 Multiple
Groups: Analysis of Variance (ANOVA) 10.1-10.3
NOTE: Spring
Break March 27-31
Week 11
4/4 21 Multiple Groups: ANOVA 10.4-10.8
·
Generalized
F Tests
·
ANOVA
and Regression
4/6 22 Summary
and Review of Hypothesis Testing
Week 12
4/11 23 Exam #2
4/13 24 Bivariate (Simple) Regression and Correlation ch 16
·
Linear
relationships and regression lines
·
Plotting
and Scattergrams
PART III: POWERFUL STUFF – ELABORATION
AND REGRESSION
Week 13
4/18 25 Bivariate (Simple) Regression and Correlation ch 16
·
Properties
of the Least Squares Fit
·
The
coefficient of determination: r2
·
The
correlation coefficient: Pearsons r
4/20 26 Elaboration & Multivariate Association ch
17
·
Elaborating
bivariate tables
·
Interpreting
partial tables
·
Partial
Gamma (Gp )
Week 14
4/25 27 Multiple
Regression ch 18
·
Introduction
to Multiple Regression
·
Regression
Assumptions: Bivariate Normality, Linearity, and Homoscedasticity
4/27 28 Inference in Multiple Regression
·
Correlation,
Causality, and Conditional Relationships
·
Dichotomous
indicator or “dummy” variables
·
Advanced Topic: Limited Dependent Variables
·
Advanced Topic: Modeling Interaction with Cross-Product Terms
Week 15
5/2 29 Summary and Review: Inference and Elaboration
·
Using
Statistics in your own Research
·
Your
next statistics course…
5/4 30 Final Projects Due
Sociology 3802 - Uggen
Tentative
Schedule for Spring 1999 Labs
1. Jan 17-18 No
labs
2. Jan 24-25 Introductions;
Exploring an SPSS data file pp
56-57
[GET FILE; FREQUENCIES,]
3. Jan 31-1 SPSS pp
58-59
[DESCRIPTIVES;
HISTOGRAMS; RECODE; COMPUTE; SELECT]
4. Feb 7-8 Work
on Assignment #1;
5. Feb 14-15 Discuss
Assignment #1
6. Feb 21-2 Review
for Exam #1 pp
174
7. Feb 28-9 Open
8. Mar 6-7 SPSS
T-TESTS pp
225-32
9. Mar 13-14 SPSS
CROSSTABS
10. Mar 20-21 Work
on Assignment #2; Crosstabs and c2 tests pp 299-304
Mar 27-8 SPRING BREAK - NO LABS
11. Apr 3-4 Review
Assignment #2
12. Apr 10-11 ONEWAY
ANOVA; Review for Exam #2 pp
253-7
13. Apr 17-18 Correlation
and Simple Regression pp
407-410
14. May 1-2 Multiple
Regression pp
469-472
NOTE: The
above schedule is Uggen’s best guess about the timing
and content of your lab sessions. Each
lab instructor, however, will tailor her or his presentation to the specific
needs of students, so please regard the scheduling as tentative.
Uggen's