1. Research & the Role of Statistics 2 1. Research & the Role of Statistics 2. Variables & Levels of Measurement

1. The Structure of Research & The Role of Statistics

Begin with Broad Questions Most social research originates from some general problem or question Curious/troubled about some aspect of society

Begin with Broad Questions Example: What influences how a child does in school? General question that can’t be adequately addressed by 1 study

Narrow Down, Focus In Next, we come up with a more specific research question one we can realistically address Here, a review of the scientific literature can serve as a guide Tells you what other researchers have found Gives “bearing” to your research study

Narrow Down, Focus In Example: What is the relationship between family structure and school performance?

Narrow Down, Focus In Also can be stated as a causal theory – an explanation of the relationships b/t phenomena Example: Children with more parental support/guidance will tend to perform better in school.

Theory Children with more parental support/guidance will tend to perform better in school. Underlined terms are concepts – abstract ideas concepts are ambiguous

Operationalize operationalize – define a concept in a way that it can be measured

Operationalize Put another way: turning concepts into… variables something measurable any trait that can change values from case to case Some concepts easier to operationalize than others Examples: Parental support/guidance  # parents in home (1 or 2) School performance  GPA (1 to 4)

Group Exercise: “Operationalization” Working with the person (or 2) closest to you, come up with variables (something measurable) that could be used as indicators of the following concepts: Healthy lifestyle (of an individual) Economic health of Duluth Success of UMD grads

Operationalize Hypothesis: derived from theory statement about a relationship between variables therefore: it is more specific/exact than a theory it is testable

Operationalize Hypothesis example: Independent variable (x) Students living in homes with 2 parents/guardians will tend to have higher GPA’s than students from 1-parent households. Independent variable (x) cause (i.e., # of parents) Dependent variable (y) effect or outcome measure (GPA) x  y

Observe Observations allow for hypothesis testing Science is a systematic method for explaining empirical phenomena Empirical means measurable & observable

Observe Research methods are the tools used at this stage How are data to be sampled & gathered? Lab experiment? Survey? Analysis of existing data? Observations produce data

Analyze Data & Reach Conclusions Our focus in this class: hypotheses are tested by comparing observations to theoretical predictions Statistical procedures give the ability to tell: whether the data support our hypotheses & by extension, whether our theory is supported

Analyze Data & Reach Conclusions Two classes of statistical techniques: Descriptive – used to summarize/organize/ describe data. Example: What is the avg. # of hours per week people spend on cell phones?

Analyze Data & Reach Conclusions Two classes of statistical techniques: 2. Inferential – used to generalize findings from a sample to a population Example: polling just a few hundred voters to predict how a presidential election will turn out.

Generalize Back to Questions What do the results tell us about our original broader question? Determined by: How theories are operationalized The nature of the observed sample

2. Variables & Levels of Measurement Reminder: VARIABLES are any trait that can change values from case to case Attribute – specific value on a variable Example: sex has 2 attributes, male & female Variables ALWAYS should: be exhaustive – variables should consist of all possible values/attributes have mutually exclusive attributes; no case should be able to have 2 attributes simultaneously

3 Levels of Measurement Nominal – mutually exclusive & exhaustive categories that cannot be meaningfully ordered (e.g., sex, religion, political affiliation) Categories need to be relatively homogenous

3 Levels of Measurement A B C D *With parents *w/Room- mates *Dorms Scales for Measuring Students’ Living Arrangements A B C D *With parents *w/Room- mates *Dorms *Away from Home *Apartment *House *Apartmnt *Other

NOT MUTUALLY EXCLUSIVE 3 Levels of Measurement Scales for Measuring Students’ Living Arrangements A B C D *With parents *w/Room- mates *Dorms *Away from Home *Apartment *House *Apartmnt *Other NOT MUTUALLY EXCLUSIVE

NOT MUTUALLY EXCLUSIVE 3 Levels of Measurement Scales for Measuring Students’ Living Arrangements A B C D *With parents *w/Room- mates *Dorms *Away from Home *Apartment *House *Apartmnt *Other NOT MUTUALLY EXCLUSIVE NOT EXHAUSTIVE

NOT MUTUALLY EXCLUSIVE 3 Levels of Measurement Scales for Measuring Students’ Living Arrangements A B C D *With parents *w/Room- mates *Dorms *Away from Home *Apartment *House *Apartmnt *Other NOT MUTUALLY EXCLUSIVE NOT EXHAUSTIVE NOT HOMOGENOUS

NOT MUTUALLY EXCLUSIVE 3 Levels of Measurement Scales for Measuring Students’ Living Arrangements A B C D *With parents *w/Room- mates *Dorms *Away from Home *Apartment *House *Apartmnt *Other NOT MUTUALLY EXCLUSIVE NOT EXHAUSTIVE NOT HOMOGENOUS O.K.

3 Levels of Measurement 2. Ordinal – categories can be ranked in addition to being categorized. Example: “I would rather get beat with a lead pipe than attend this class.” 1 = strongly disagree 2 = disagree 3 = neutral 4 = agree 5 = strongly agree

3 Levels of measurement What’s Wrong with This Question: How long have you been attending UMD? 1 to 11 months 1 to 2 years 2 to 3 years 3 to 4 years 5 or more years

3 Levels of measurement 3. Interval-Ratio – categorical units are equal Examples: prison sentence in months, population of Duluth, age This level permits all mathematical operations (e.g., someone who is 34 is twice as old as one 17) Pointy headed issue Interval = no meaningful zero point Ratio = meaningful zero point DOESN’T MATTER ONE BIT FOR DATA ANALYSIS

Group Exercise Research Hypothesis = Males who experience hair loss become more likely to experience depression. What is the IV? What is the level of measurement for this variable? What is the DV? Operationalize the DV so that it is measured at the nominal, ordinal, and interval/ratio levels.