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Social Science Research Quantitative Methods I

SYA 6315-U01 / Fall 2013

Dr. María Aysa-Lastra

Department of Global and Sociocultural Studies

T 2:00 p.m. – 5:00 p.m. / SIPA 200 (Lab)

Getting in touch

Tel: 305/348-2258

Office hours: T 12:00 -1:00 pm (or by appointment)

Location: SIPA 311

E-mail: aysam@fiu.edu

Objective

This course provides a graduate-level introduction to applied statistics within the

framework of social research and analysis. The course complements the graduate

seminars in social theory and social research methods. Its objective is to present basic

conceptual and practical tools in social statistics so that—whether or not you intend to

pursue a career of doing quantitative studies—you’ll be better equipped, first, to critically

assess social (and policy) research carried out from a wide array of methodological

perspectives; and second, to make sound methodological decisions and wise

interpretations in carrying out your own research projects.

If you complete your assignments, work with your team, understand the materials

provided, read the assigned material before class and attend all lectures, by the end of the

semester, you should be able to:

Design a research project

Design a sound and viable sample

Critique a research design

Analyze and interpret data

Perform a hypothesis test

Perform and interpret multivariate analysis

Use statistical software

Books, software & supplements

The required books are:

Moore, McCabe & Craig, Introduction to the Practice of Social Statistics, 7th

ed.

Utts, Seeing Through Statistics, 3rd

ed.

Acock, A Gentle Introduction to Stata, 3rd

ed.

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Strongly recommended as supplementary reading are:

Ragin and Amoroso, Constructing Social Research, 2nd

ed.

Hamilton, Statistics with Stata Version 10

Allison, Multiple Regression. A Primer

Fox, Regression Diagnostics

Achen, Interpreting and Using Regression

Pampel, Logistic Regression. A Primer

Associated with Moore, McCabe & Craig there are a couple of web sites (open access:

http://www.whfreeman.com/ips7e; and access code required:

http://www.yourstatsportal.com ) and a CD-ROM that contain helpful materials, not least

of which are conceptually-oriented quizzes on each chapter and “applets” that permit

hands-on, interactive learning. In addition, there is an excellent PBS-Annenberg video

series, “Against All Odds: Inside Statistics.” This series is available on the shelves in the

audio-visual section of the Green Library (5th

floor).

Software—Stata Version 12: www.stata.com. Discounted purchase via FIU/Stata

GradPlan. Stata is installed on computers in the SIPA Lab and it is available through FIU

elabs: http://elabs.fiu.edu. Read the Quick Start Guide and install Microsoft Remote

Desktop Connection Client 7.0 in your computer.

UCLA’s Academic Technology Services has created a website that makes available an

impressive set of free, downloadable materials for learning statistics in tandem with Stata

or SPSS, SAS, or specialized statistical software. The subsite

http://www.ats.ucla.edu/stat/seminars/ contains introductions to these and other statistical

software programs, including movies. The Stata subsite is located at:

http://www.ats.ucla.edu/stat/stata/.

Software, though, is just a tool. The focus of this course is learning statistics as one way

to describe and understand significant aspects of social relations.

Classroom policy, projects, exams & grades

It is assumed that students will attend all class sessions & arrive on time.

Cell phones must be turned off during class sessions, and using your lab computer

for emailing or internet browsing during that time is prohibited.

Questions, comments & discussion are enthusiastically encouraged.

Graded assignments:

o Students are responsible for all materials covered in the assigned readings

& problems, as well as all materials covered in class sessions.

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o All graded assignments must be completed on time in order to earn a

passing grade in the course. Late assignments will not be graded.

o Moore, McCabe and Craig homework problems. These include practice

not only in solving statistical problems but in using and interpreting

statistics wisely. Hands-on practice, done virtually every day, is the only

way to learn statistics (and software) as well and as fast as we need to do

in this course. The Moore, McCabe and Craig problems are meant to

foster active learning. In that spirit, odd-numbered exercises have

answers, but not step-by-step solutions, in the back of the book. Some of

them, moreover, are pegged to the web site’s and CD-ROM’s interactive

applets, which in general should be used frequently for active learning of

concepts. Grading: pass/fail and worth 10% of the final grade.

Assignments are due on the dates indicated in the class schedule.

Present only the Stata commands, properly formatted tables & your

interpretation of the output; do not present the statistical output itself.

o One research project based on a data set to be chosen in consultation with

the instructor. Students will use Stata to conceptualize and apply the

statistical methods we will have covered, and will interpret the results as

well as explore the pro’s and con’s of statistical social research.

Grading: The project is worth 30% of the course grade. The project is due

at the start of the class session on November 26.

o Two take-home exams, which will combine statistical problems with

essays focusing on the development of sober judgment in selecting,

applying, interpreting, and critiquing statistics.

Grading: each take-home exam is worth 30% of your course grade (for a

total of 60%). Exam one is due on Oct 15 and Exam two is due on Dec 3.

Preparing for class sessions

Each class session will cover the minimum technical information that’s necessary

to learn statistics and Stata, and the maximum possible to put social statistics within the

frameworks of social research methodologies.

Regarding the basics of statistics, we’ll stick closely to Moore, McCabe and

Craig’s textbook presentation, emphasizing the broadest conceptual issues. At the start of

each session we’ll review some of the homework problems and/or the take-home exam

you will have completed. As much as possible we’ll use the problems and exams to raise

the big issues about doing social research.

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Here’s how to prepare for each session:

Complete the assigned Moore, McCabe and Craig problems and/or the assigned

take-home exam or project.

Review the “Social Research Study Questions” and the “Statistical Methods:

Some Pro’s & Con’s” (both of which are attached to the syllabus) before the first

class session and throughout the semester. We’ll refer to them frequently.

The assigned readings from Moore, McCabe & Craig should be read before each

session, then should be thoroughly covered when doing the homework problems

(including use of the instructor-supplied, Stata-formatted text data sets).

Do the web or CD-ROM quiz corresponding to each Moore, McCabe & Craig

chapter assignment to make sure you’ve mastered the course material. The

quizzes, however, will not be graded.

Everything else: Do whatever works best for you. In my experience working in

study groups is the best way to learn statistics.

Policy on make-up examinations, assignments or performance measures

In case the student is experiencing an unexpected circumstance, he/she should

communicate to the instructor before the due date of the weekly assignment or exam and

asked for a reasonable extension. All students must take the two take-home exams.

FIU’s Policies and Codes

Florida International University is a community dedicated to generating and imparting

knowledge through excellent teaching and research, the rigorous and respectful exchange

of ideas, and community service. All students should respect the right of others to have

an equitable opportunity to learn and honestly to demonstrate the quality of their learning.

Therefore, all students are expected to adhere to a standard of academic conduct, which

demonstrates respect for themselves, their fellow students, and the educational mission of

the University. All students are deemed by the University to understand that if they are

found responsible for academic misconduct, they will be subject to the Academic

Misconduct procedures and sanctions, as outlined in the Student Handbook.

Please for additional information see: Policies on Academic Misconduct

Other Policies and Codes

Academic Calendar, please note that November 4 is the last date to drop the course with

a DR grade.

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Schedule

Aug. 27

Week 1 Data Distributions

Required Moore, McCabe & Craig, Introduction and chapter 1

See “Social Research Study Questions” & “Statistical Methods: Some

Pro’s & Cons” attached to syllabus

Utts, chapters 1 and 2

Acock, chapters 1 and 5

Recommended Ragin & Amoroso, chapters 1 & 2

Assignments

(due Sep 3)

1) Go to the website for “ASR Manuscript Submission Information

for Authors” or the main journal in your discipline and navigate

to the “Preparation Checklist for Manuscripts”. Provide a

summary of the main items and bring an example using each

type of text citation, and bibliographic reference.

2) Provide an example of a table published in any academic

quantitative research paper of your interest.

3) Moore, McCabe & Craig problems 6th

ed: 1.12, 1.17, 1.21, 1.37,

1.46

Moore, McCabe & Craig problems 7th

ed: 1.14, 1.17, 1.21, 1.41,

1.46

4) Submit a topic and a question for your quantitative research

project.

Sep 3

Week 2 Data Distributions (continued)

Required Utts, chaps. 7, 8 and 9

Moore, McCabe & Craig, chapter 1

Acock, chapters 1 and 5

Recommended Ragin & Amoroso, chapter 3

Assignments

(due Sep 10)

1) Answer the following questions: a) Which are the characteristics

of a well-designed graph? b) Which are the most common

problems in plots, graphs and pictures? c) Which are the

characteristics of a well-designed table?

2) Moore, McCabe & Craig problems 6th

ed: 1.57, 1.58, 1.62, 1.65,

1.82, 1.83, 1.84, 1.86, 1.87, 1.88; 1.111, 1.120,1.122, 1.140,

1.141, 1.142, 1.146

Moore, McCabe & Craig problems 7th

ed: 1.69, 1.70, 1.73, 1.74,

1.80, 1.90, 1.91, 1.92; 1.119, 1.127, 1.128, 1.146, 1.147, 1.148,

1.151

3) Study questions: Why do univariate distributions matter—in

terms of substantive issues in social science and in terms of

statistics? Why should we graph a univariate distribution before

we numerically summarize it? What are the advantages of the 5-

number distribution?

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Sep 10

Week 3 Data Relationships: Bivariate Distributions

Required Utts, chapters 10 and 11

Moore, McCabe & Craig, chapter 2

Acock, chapter 6

Recommended Ragin & Amoroso, chapters 6 and 7

Assignments

(due Sep 17)

1) Moore, McCabe & Craig problems 6th

ed: 2.6, 2.7; 2.30, 2.31,

2.48; 2.58, 2.59, 2.60, 2.61

Moore, McCabe & Craig problems 7th

ed: 2.24, 2.25; 2.47, 2.48,

2.58; 2.73, 2.74, 2.75, 2.76

2) Study questions: What can be misleading about measures of

correlation and regression, and why? When might there be a

strong bivariate relationship but a low correlation or regression

coefficient? What are the advantages of regression versus

correlation

Sep 17, Sep 24

Week 4 Data Relationships: Bivariate Distributions

Required Moore, McCabe & Craig, chapter 2

Acock, chapter 6

Recommended Utts, chapter 12

Assignments

(due Oct 1)

1) Moore, McCabe & Craig problems 6th

ed.: 2.91, 2.104; 2.111,

2.112, 2.113; 2.123, 2.126; 2.159

Moore, McCabe & Craig problems 7th

ed.: 2.105, 2.114; 2.125,

2.126, 2.127; 2.136, 2.137; 2.173

2) Study questions: What are the basic ways of establishing and

explaining causation? What critical questions must we ask

concerning the possible relationship between two variables?

Oct 1

Week 5 Producing Data

Required Moore, McCabe & Craig, chapter 3

Utts, chapter 3, 4 and 5

Acock, chapters 2 and 3

Recommended Ragin & Amoroso, chapters 4 and 5

Assignments

(due Oct 8)

1) Moore, McCabe and Craig problems 6th

ed: 3.17, 3.18; 3.52,

3.53, 3.56, 3.61, 3.65; 3.82, 3.83, 3.84; 3.120, 3.127.

Moore, McCabe and Craig problems 7th

ed: 3.17, 3.18; 3.52,

3.53, 3.58, 3.63, 3.67; 3.82, 3.83, 3.84; 3.126, 3.121.

2) Study questions: What is “statistical” significance? Give a

social-science example of how it can be different from

“practical” or “theoretical” significance? What is bias? What is

variability? Why is randomization important? Why is

comparative design important? What are the advantages of

experimental research and the reasons for these advantages?

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What are the disadvantages of experimental research? What are

the main sampling methods? What are the advantages and

disadvantages of each sampling method? What are possible

“sampling” and “non-sampling” sources of error in surveys?

3) EXAM 1 assigned: The exam will cover the materials in

chapters 1, 2 and 3 of the Moore, McCabe and Craig textbook

and the assigned chapters from Utts.

Oct 8

Week 6 Probability & inference

Required Moore, McCabe & Craig, chapter 4

Recommended Utts, chapter 15, 16 and 17

Assignments

(due Oct 15)

1) READ CHAPTER 4

2) Study questions (OPTIONAL, for extra credit): Why is

randomization important? What is a random variable? What is

a probability distribution? Why is the reason for using the term

“expected value of random variable” instead of “mean of a

random variable”? What is the Law of Large Numbers? How

many trials are need to guarantee a mean outcome close to the

population mean? What are “independent observations” (or

events), and when can this requirement be relaxed? What is

“conditional probability,” and what would be a social-science

example?

3) EXAM 1 due: bring a hard copy of your answers at the start of

class session.

Oct 15

Week 7 Sampling distributions

Required Moore, McCabe & Craig, chapter 5

Recommended Utts, chapter 18

Assignments

(due Oct 21)

1) Moore, McCabe and Craig problems 6th

ed: 5.9, 5.10, 5.11, 5.12,

5.24, 5.26; 5.41, 5.61; 5.64.

Moore, McCabe and Craig problems 7th

ed: 5.41, 5.42, 5.43,

5.44, 5.56, 5.60, 5.80

2) Study questions: What is a sampling distribution? What is a

population distribution? What would be a social-science

example of both? What is a count and a sample proportion, and

a social-science example of each? What is the “binomial

setting,” and what is a social-science example? What is a

binomial distribution and a sampling distribution of a count?

When should we use a binomial sampling distribution? Why are

sample means used in statistical inference? What is the sampling

distribution of a sample mean, and what is a social-science

example? How do we compute the mean and standard deviation

of a sample mean? What is the Central Limit Theorem, and why

is it important? Why is it that the sample mean of an SRS from

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a normal population has a normal distribution, and what

principle does this illustrate?

Oct 21

Week 8 Introduction to inference

Required Moore, McCabe & Craig, chapter 6

Acock, chapter 7

Recommended Utts, chapter 20, 21, 22 and 23

Assignments

(due Oct 29)

1) Moore, McCabe and Craig problems 6th

ed: 6.116, 6.120, 6.125,

6.126, 6.132.

Moore, McCabe and Craig problems 7th

ed: 6.116, 6.120, 6.125,

61.26, 6.132

2) Study questions: What is “statistical inference”? For what kinds

of data sets is it valid or invalid? What is the difference between

statistical significance and “practical” or “theoretical”

significance? What is a confidence interval, and how is it

computed? What are the data requirements for a valid

confidence interval, and how do we check these requirements?

How can we reduce a confidence interval? How do we test a

hypothesis? What is wrong with accepting a null hypothesis?

What is wrong with accepting an alternative hypothesis? What

is a P-value? What is wrong with “searching for statistical

significance”? When should statistically insignificant results be

reported and explained? What are Type I and Type II errors, and

what is an example of each?

Oct 29

Week 9 Inference for distributions

Required Moore, McCabe & Craig, chapter 7

Acock, chapter 7

Recommended Utts, chapter 20, 21, 22 and 23

Assignments

(due Nov 5)

1) Moore, McCabe and Craig problems 6th

ed: 7.113, 7.115, 7.130,

7.131, 7.132, 7.133.

2) Moore, McCabe and Craig problems 7th

ed: 7.113, 7.115, 7.134,

7.135, 7.136, 7.137.

3) Study questions: What is a t distribution, when is it used, and

how is it computed? How do t distributions differ from z

distributions, and at one point do they become more or less

identical? When do we use one-sample and two-sample t tests,

and what is a social-science example for each? What are the

data requirements for such tests? What in general are test

alternatives if the data requirements are not met?

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Nov 5

Week 10 Inference for proportions

Required Moore, McCabe & Craig, chapter 8

Acock, chapter 7

Recommended Utts, chapter 19

Assignments

(due Nov 12)

1) Moore, McCabe and Craig problems 6th

ed: 8.57, 8.64, 8.77,

8.78, 8.79, 8.83

Moore, McCabe and Craig problems 7th

ed: 8.61, 8.74, 8.95,

8.96, 8.97, 8.101

2) Study questions: What is a social-science example for single

proportion and for two proportion inference? What are the data

requirements?

Nov 12

Week 11 Inference for two-way tables

Required Moore, McCabe & Craig, chapter 9

Acock, chapter 6

Recommended Utts, chapter 12

Assignments

(due Nov 9)

1) Moore, McCabe and Craig problems 6th

ed: 9.6, 9.7, 9.15, 9.16,

9.26, 9.36, 9.42, 9.44

Moore, McCabe and Craig problems 7th

ed: 9.26, 9.27, 9.33,

9.34, 9.42, 9.50, 9.52

2) Study questions: What are the data requirements for two-way

tables? What is a social-science example of a two-way table?

What is Simpson’s Paradox, what is the reason for it, and how

can we guard against it? What is the chi-square statistic? How

do we test a hypothesis for a two-way table?

Nov 19

Week 12 Inference for regression

Required Moore, McCabe & Craig, chapter 10

Acock, chapter 8

Recommended Utts, chapter 10

Allison book

Assignments

(Optional)

1) Moore, McCabe and Craig problems 6th

ed: 10.6, 10.7, 10.8,

10.9, 10.10, 10.39, 10.40, 10.41, 10.47, 10.48, 10.49, 10.51

Moore, McCabe and Craig problems 7th

ed: 10.6, 10.7, 10.8,

10.9, 10.10, 10.37, 10.38, 10.39, 10.45, 10.46, 10.47, 10.49

2) Study questions: What is simple linear regression? How does it

differ from correlation? When might there be a strong bivariate

relationship but a weak correlation or regression coefficient?

What are the data requirements for regression? What do the

following mean: DATA=FIT + RESIDUAL? How do we test a

hypothesis for a regression coefficient? What does it mean if the

plotted residuals of a regression model are not randomly

distributed?

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Nov 26

Week 13 Inference for regression (continued)

Required Moore, McCabe & Craig, chapter 11

Acock, chapter 8

Recommended Utts, chapter 10

Allison book

Assignments

(Optional)

1) Study questions (OPTIONAL, for extra credit): What is the

advantage of multiple regression over simple regression?

Explain why or why not a strong/weak bivariate relationship

may not result in a strong/weak multivariate relationship,

including what this has to do with our previous reading on causal

relations?

2) Bring a hard copy of your assigned research project

3) EXAM 2 assigned

Dec 3 (Final exam week)

Exam two 1) EXAM 2 due: print a hard copy of your answers and drop it in

my mail box (SIPA 3rd

floor) by noon.

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Social Research Study Questions

1. What is social research? What are the principal differences between social

research and other ways of representing social life?

2. What is the scientific method? What steps does the scientific method apply in

conducting social research?

3. What is a research strategy? What are the differences between research strategies

that paticularize and those that generalize? What are the potential similarities

between such strategies?

4. What is the social construction of reality? How does it pertain to the scientific

method, social research/research strategies in general, and to other ways of

representing social life—including the promises and risks of the various

approaches?

5. What are data? What are interplays between data and the social construction of

reality? Is everything worthwhile measurable?

6. What is statistics? What is the difference between descriptive statistics and

inferential statistics? How do descriptive statistics and inferential statistics

pertain to the principal kinds of research strategy?

7. What are advantages and disadvantages of using statistics in social research?

8. What are the intersections between the uses of statistics in social research and the

social construction of reality? Conversely, what are the intersections between the

“non-uses” of statistics in social research and the social construction of reality?

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Statistical Methods: Some Pro’s & Con’s

Some advantages of using statistics

Summarizes complex data

Makes assumptions explicit

Imposes explicit standards of evidence and comparison

Raises the possibility of chance associations

Emphasizes skepticism about hypotheses and findings

Facilitates the testing of competing hypotheses and the building of theories

Permits the examination of certain questions that couldn’t otherwise be examined

Some pitfalls of using statistics

The use of statistics represents a strategic tool in the social construction of reality.

Thus its use in general must be situated in the historical/geographic context of

bureaucratization, state formation and geopolitical competition, industrial/

technological revolution, commodification, and urbanization; and the biases of

statistical premises and the tendency of the statistically inclined research

establishment to claim intellectual/policy hegemony on the basis of a “scientific

approach” must be critically examined.

The use of statistics impedes the examination of certain questions that otherwise

would be examined, and obfuscates crucial kinds of social, cultural, and political

analysis.

Theory and substantive importance must guide the use of statistics (although the

data must inform the theory as well [e.g., making sense of unanticipated

nonlinearities or outliers]).

Statistical research needs to emphasize theoretical/substantive significance and

the magnitude of relationships between variables, rather than mere “statistical

significance” as narrowly defined by mainstream statistical methodology. The

research needs to recognize the arbitrariness of institutionalized significance-test

standards and to consider alternative criteria for statistical significance.

Statistical research needs to test a study’s findings, not just against its null

hypothesis but also against competing theories/hypotheses with the objective of

long-term theory building.

We need to use statistics wisely as one of many tools in social research.

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Reminders

How were the numbers produced—in the sense of culture and power, and

according to the (cultural) rules of scientific method?

Is the sample random and representative of the population? Insofar as this is not

true, then the use of inferential statistics is invalid.

What is the shape, center, and spread of the distribution? Are there outliers?

Do the numbers make sense? (adapted from Moore, The Basic Practice of

Statistics):

o What’s the explicit or implicit agenda behind them?

o Is any essential information left out?

o Are the numbers consistent?

o Are the numbers plausible, including are they too good to be true?

o Is the math correct?

o What do the numbers signifiy about the social relations being studied?

Always take “outlying” observations, “non-significant” findings, and otherwise

“contrary” findings seriously: What insights do they potentially convey about the

social relations that you’re studying, and possibly about social relations more

generally?

You’ve estimated something’s magnitude or likelihood. Don’t lose sight of

uncertainty: What’s the thing’s estimated range of magnitude or likelihood? What

does this range imply about the social relations being examined?

Are all worthwhile things measurable? What do your conclusions imply about the

social relations and public policies that you’re studying, and perhaps about social

relations and public policies in other spheres?

Benchmarks for assessing the usefulness of

any application of social statistics

Does the use of statistical methods in any given instance notably improve our

intellectual understanding of social relations and public policies?

In any given instance, what insights does the use of statistical methods provide (or

not) in comparison with insights provided by other methods of social research,

and in comparison with insights provided by other ways of interpreting the world?

A strategic point in interpreting & summarizing your study’s results

What are the wider, comparative ramifications of your study for the

understanding of social relations and social policy/political practice?