1. Ch. 2: Planning a Study

2. PICK A STUDY TOPIC something “generalizeable”
featuring social patterns
that applies to “aggregates”
(i.e., a collection of people or other units)
that is empirically observable

3. REVIEW PAST STUDIES to focus research question
for examples of research designs, measures, and techniques
to learn key ideas, factors, terms, and issues re: topic, in order to replicate, test, or extend what others have found
for examples of content and style in research reports
for FUN – to stimulate creativity & curiosity

4. Where Do You Find the Research Literature?
Peer-reviewed scholarly journal
Semi-scholarly professional publication
Practitioner magazine or newsletter
Opinion magazine
Mass market magazines for the public

5. Where to find reports on empirical research?
Scholarly journals
Books (monographs, readers, edited collections)
Government documents
Ph.D. dissertations
Policy reports
Presented papers

6. Lit Review: the Six-Step Process
Refine the topic
Design your search
Locate the research reports
Read and take notes on reports found
Organize notes, synthesize, and write the review
Create the reference list

7. FOCUSING ON A RESEARCH QUESTION
Inductive research starts with many specific observations and out of them builds generalizations or theory
Deductive research starts with a general idea or theory and “tests” it by looking at specific observations

8. Fig. 2.8: Deductive vs Inductive Approaches
IDEAS
IDEAS
Observed data
Observed data

9. THE RESEARCH PROPOSAL
In all empirical research studies, you systematically collect and analyze data
Data may be qualitative or quantitative or both
Each data form has strengths
Your goal is to fit the form of data to a specific research question and situation in a way that utilizes its strengths (46)

10. Key questions in writing a research proposal:
When to focus research question?
Universe of study?
Linear or nonlinear path?
Variables/hypotheses or cases/contexts?
How to analyze patterns in data?
Type of explanation?
Units of analysis?
Level of analysis?

11. 1. When do you focus the research question?
It depends partly on the type of data you plan to use
If quantitative, you need to have a focused question before you actually collect the data, so you know where to look
If qualitative, your question will get focused in the process of gathering and examining your data

12. 2. To what universe can you generalize a study’s findings?
Only rarely do we want to restrict our findings to the specific units or cases we actually study; instead, we want to generalize to a broader category of people, organizations, and other units

13. universe
a broad category of cases or units to which the study findings apply
e.g., if we are interested in NYC high school students, we can’t contact all high school students in the city; rather, we’ll be able to contact only a subset of them; yet we will still attempt to generalize our findings to the universe of “NYC high school students”

14. 3. Which type of research path do you follow?
A path is a metaphor for the sequence of activities you do
Generally, with quantitative data, you follow a linear path, with qualitative data, a nonlinear path
linear path: a relatively fixed sequence of steps in one forward direction, with little repeating, moving directly to a conclusion
nonlinear path: advancing without fixed order that often requires successive passes through previous steps and moves toward a conclusion indirectly

15. 4. What do you examine?
Research with quantitative data focuses on variables and the relationships among them
Research with qualitative data tends to examine a limited number of cases in-depth; concerned with discovering “meanings” of different social situations

16. Variable
Variable: a feature of a case or unit that represents multiple types, values, or levels
The variable is central idea in quantitative research
Simply defined, it’s a concept that varies
Variables are different from categories of variables, though they’re often confused

17. Types of variables
independent variable (IV): the variable of factors, forces, or conditions acting on another variable to produce an effect or change in it
dependent variable (DV): the variable influenced by and changed as an outcome of another variable
intervening: a variable that comes between the independent and dependent variable in a causal relationship

18. A 3-variable example from Durkheim’s study of suicide
Theory: married people are less likely to commit suicide than single people because they are more socially integrated
Restated in terms of variables: being married (IV) increases social integration (intervening variable), which in turn reduces the suicide rate (DV)

19. Hypothesis
Hypothesis: a statement about the relationship of two (or more) variables yet to be tested with empirical data
5 features of a causal hypothesis:
It has at least 2 variables
It specifies how the variables are connected (which is the cause, which is the effect)
It includes a time order assumption
It can be restated as a prediction
It can be supported or falsified with empirical data

20. Null hypothesis
null hypothesis: a hypothesis that there is no relationship between variables, that they do not influence one another
If the evidence supports the null hypothesis, you are forced to conclude your alternative hypothesis is false
But if the evidence rejects the null hypothesis, then the alternative hypothesis remains a possibility
Null hypothesis is used because researchers are very cautious – similar to the idea of innocent until proven guilty or reasonable doubt

21. 5. How do you look for patterns in the data?
With quantitative data, you use charts, tables and statistics to see patterns; you connect the patterns with your research question.
With qualitative data, you identify patterns (sequences, cycles, contrasts) in the data (observed events, conversations, situations) as they appear in a specific context.

22. 6. What type of explanation will you use?
causal explanation: a type of research explanation in which you identify one or more causes for an outcome, and place cause and effect in a larger framework
Used in both quantitative and qualitative research, but more common in quantitative
grounded theory: ideas and themes that are built up from data observation
More common in research using qualitative data

23. 7. What are the units of analysis of your study?
unit of analysis: the case or unit on which you measure variables and gather data
Units of analysis influence how to gather data and the level of analysis

24. 8. What is the level of analysis of your study?
level of analysis: the level of reality to which explanations refer, micro level to macro level
it’s a mix of the number of people, the expanse of geographic space, the scope of the activity the length of time
Level of analysis influences assumptions, concepts and theories you will use, as well as the appropriate units of analysis

25. Warning: Avoid Spuriousness
spuriousness: when two variables appear to be causally connected but in reality, they are not because an unseen third factor is the true cause

26. Fig. 2.11 Spuriousness Example
Relationship between Illegal Drugs & Suicide
Illegal
drugs
Observed association
Suicide
Emotional
problems &
community
disorder
True cause