Midterm (Lectures 1-7)

Question 1

Lecture 1: #7 Describe the role of tradition and authority as sources of secondhand knowledge.

Answer 1

Tradition: “things that everybody knows”; passed on from generation to generation; expected within family & culture
Authority: knowledge described by an expert in the field

Question 2

Lecture 1: #8 Describe and illustrate each of the following errors in inquiry: Inaccurate observations, Overgeneralization, Selective Observation, and Illogical Reasoning

Answer 2

Inaccurate observation: Did you see what you thought you saw? Holes in research due to lack of paying attention; failure to correctly observe.
Overgeneralization: Seeing a pattern and applying it to every single similar instance. Example: Thinking that all college students wear oversized t-shirts with shorts.
Selective observation: Tunnel vision; You only see the information that fits in line with your pattern, ignoring all incoming information.
Illogical Reasoning: “Exception to prove the rule”; Gambler’s fallacy: thinking they will win if they just keep gambling.

Question 3

Lecture 1: #16 Differentiate independent and dependent variables by definition and example, and show how they contribute to causality.

Answer 3

Independent variable influences (causes) another variable. Dependent variable is the result (consequence) of the independent variable.

Question 4

Lecture 1: #17 Compare idiographic and nomothetic explanations.

Answer 4

Idiographic: detailed description of a single case.
Nomothetic: general or broad explanation applied to a large population

Question 5

Lecture 1: #18 Compare induction and deduction as ways of developing theories.

Answer 5

Inductive approach: starts with observations first; then looks for themes or patterns; finally, uses that info to create a theory. (Observations —— Theory)
Deductive approach: starts with theory first; then leads to a hypothesis statement; ends with observations. (Theory —— Observations)

Question 6

Lecture 2: #1 List three functions of theory for research.

Answer 6

1. Prevents being taken in by flukes.
2. Makes sense of observed patterns in ways that can suggest other possibilities
3. Directs research efforts

Question 7

Lecture 2: #2 Define paradigm.

Answer 7

A frame of reference used to interpret our observations

Question 8

Lecture 2: #4 Provide synopses for each of the following paradigms: Early Positivism, Conflict, Symbolic Interactionism, Ethnomethodology, Structural Functionalism, Feminist, and Critical Race Theory. (Be prepared to answer 3)

Answer 8

Early Positivism: Comte’s view; science can replace religion by basing knowledge on observations.
Conflict: Marx’s view; social behavior has two parts: Attempt to dominate others, Attempt to avoid domination
Symbolic Interactionism: interactions require understanding through language
Ethnomethodology: people are continuously trying to make sense of the life they experience; violating social norms is a technique of Ethnomethodology
Structural Functionalism: society can be viewed as an organism; social systems are made up of parts that make up the whole
Feminist: focuses on gender differences; draws attention to the oppression of women
Critical Race Theory: developed in the 1970s by civil rights activists as a commitment to racial justice; introduced the concept of “interest convergence”: laws will only be changed to benefit African Americans if those changes further the interests of whites.

Question 9

Lecture 2: #6 Show the role of theory, operationalization, and observation in the traditional model of science.

Answer 9

Theory: studying what is known about the topic
Operationalization: defining important variables and how we will measure them
Observation: going out and collecting the data

Question 10

Lecture 2: #8 Differentiate inductive from deductive reasoning by definition and example.

Answer 10

Inductive: qualitative in nature; starting with something specific and ending with a general theory.
Deductive: quantitative, numerical data; starts with theory and ends with specific data (traditional model of science)

Question 11

Lecture 3: #1 Describe and illustrate the ethical issues involved in: voluntary participation, no harm to subjects, anonymity and confidentiality, the researcher’s identity, and reporting.

Answer 11

Voluntary participation: informed consent- subjects must be given a full understanding of the possible risks
No harm to subjects: no physical, mental, or emotional harm should take place in a study; participants must leave the study exactly as they were before
Anonymity: identities of participants cannot be shared
Confidentiality: responses cannot be made public
Researcher’s identity: if deception takes place, participants must be informed about the true nature of the research at the end of the study
Reporting: researchers must be honest about their findings and research

Question 12

Lecture 3: #2 Describe the role of the Institutional Review Board (IRB).

Answer 12

IRBs review research proposals involving humans to guarantee the rights and interests of the participants are protected

Question 13

Lecture 3: #5 Describe two ways in which ethical and political concerns differ.

Answer 13

Ethical concerns: deal mostly with methods in research

Political concerns: deal mostly with the substance and use of research

Question 14

Lecture 4: #4 Describe the three main criteria for nomothetic, causal relationships.

Answer 14

1. Relationship (or correlation) between two or more variables
2. One variable has to come before the other in terms of time (the cause before the effect)
3. Need the relationship to be nonspurious (no third variable can interfere)

Question 15

Lecture 4: #7 Define and illustrate the ecological fallacy.

Answer 15

Definition: assuming something learned about a group says something about the individuals in the group.
What I learn about a group, I need to understand.
What I learn about that group cannot be limited to an individual, it has to apply to the entire group.

Question 16

Lecture 4: #8 Define and illustrate reductionism.

Answer 16

Simplifying an explanation too much; does not give enough information and is overly nomothetic and broad.

Question 17

Lecture 4: #11 Differentiate among the three types of longitudinal studies, trend, cohort, and panel by definition and example.

Answer 17

Trend study: a steady flow of information; tracking changes within a population over time.
Cohort: tracking changes in a subpopulation over time; for example, tracking an age group over time as they grow; may not be the same group every time
Panel: studying the exact same individuals at every time point.

Question 18

Lecture 4: #14 Identify the basic elements of a research proposal.

Answer 18

1. Problem or objective
2. Literature review
3. Selecting subjects for study
4. Measurement
5. Data collection
6. Methods analysis
7. Schedule
8. Budget
9. IRB

Question 19

Lecture 5: #14 Explain why attributes of a variable should be exhaustive and mutually exclusive, and give examples of each.

Answer 19

Exhaustive: Response options must be exhaustive so each participant can identify themselves; always list “Other” after you have exhausted all other options just in case
Mutually exclusive: you only want participants to choose ONE option; give such direct response options that there is no room for them to choose multiple

Question 20

Lecture 5: #15 Differentiate the following four levels of measurement and give an example of each: nominal, ordinal, interval, and ratio.

Answer 20

Nominal: label or name; classification. Example: “What state were you born in?”
Ordinal: rank order; Example: Range of “Strongly agree” to “Strongly disagree”; can only tell if scores are higher or lower than one another
Interval: rank order with equal distance between values; Example: the difference between 40 and 50 degrees is the same distance between 70 and 80 degrees; we can now tell how much more or less someone scores; there is NO zero-point
Ratio: has all of the above qualities combined; there IS a possibility of a zero-point; Example: it makes sense for someone to answer: “I have no kids” when asked how many they have.

Question 21

Lecture 5: #19 Define reliability and compare these strategies for improving the reliability of measures: test-retest method, split-half method, using established measures, and reliability of research workers.

Answer 21

Test-retest: administering test on multiple occasions and seeing if the answers are the same later
Split-half method: splitting measure in half and applying it to the group; making more than one measurement
Using established measures: find a measure that is proved to have sound reliability.
Research worker reliability: making sure everyone is consistent in administering tests and interacting with participants; stable scoring ability

Question 22

Lecture 5: #20 Define validity and compare these types of validity: face validity, criterion-related validity, construct validity, and content validity.

Answer 22

Validity: are you measuring what you set out to measure?
Face validity: does this question make sense and is it related to the topic we are studying? Does it make sense to include this in our study?
Criterion-related: how well our measure predicts the outcome of another measure
Construct: there is some sort of theoretical relationship between your topic and other topics; truly measuring what you set out to measure; Example: comparing martial satisfaction to infidelity
Content: making sure the measure includes all that its name implies; Example: If I were giving a mathematical ability test I would give questions and items related to all forms of math

Question 23

Lecture 6: #3 Differentiate index from scale by definition and example.

Answer 23

Index: adding across, an accumulation of scores
Scale: pattern-based score

Question 24

Lecture 6: #11 Describe three strategies for handling missing data in index construction.

Answer 24

1. Omit, cut out
2. Treat missing data as a possible response
3. Interpret or analyze to see why there is missing data
4. Assign the mean for the average score of that particular item

Question 25

Lecture 6: #13 Describe the logic and procedures of the Bogardus Social Distance scale.

Answer 25

Measuring a participant’s willingness to interact with someone who is different than them

Question 26

Lecture 6: #16 Describe the logic and procedures of the Semantic differential.

Answer 26

basically a Likert scale; placed between two different views (strongly agree——strongly disagree)

Question 27

Lecture 6: #17 Describe the logic and procedures of Guttman scaling.

Answer 27

The true definition of a scale; intensity scale: some scores will be stronger, some will be weaker; assigning score based on pattern.

Question 28

Lecture 7: #1 Define sampling

Answer 28

Selection of who or what you are going to studying

Question 29

Lecture 7: #3 Describe and illustrate each of the following types of nonprobability sampling: reliance on available subject sampling, purposive (judgmental) sampling, quota sampling and snowball sampling.

Answer 29

Reliance: sample of convenience, using those readily available and not going out of your way to fins subjects.
Purposive (judgmental): researcher has some knowledge of the population they want to study; specifically go out of the way to find deviant cases
Quota: best way to get a representative sample; researcher still has bias over who is being chosen and selected; makes sure the data collected is still representative of the small group.
Snowball: the “refer a friend” method; used when the population is difficult to reach.

Question 30

Lecture 7: #4 Describe the role of the informants in nonprobability sampling and provide advice on how to select them.

Answer 30

• Well-versed in a group or society
• Used for starting-knowledge on the study
• Can color your interpretation of the group you are studying
• Atypical because of their willingness to talk about the group

Question 31

Lecture 7: #6 List two advantages of probability sampling over nonprobability sampling.

Answer 31

Probability sampling: most effective method for population selection and eliminates researcher bias (also, permits estimates of sampling error)

Question 32

Lecture 7: #10 Define sampling frame and restate the cautions regarding making generalizations from sampling frames to populations.

Answer 32

Sampling frame: list of elements that make up the larger population then used to choose participants. Example: Class roster or phone book
Cautions: Lists like a roster or phone book could be outdated; Every person should have an equal chance to participate; People will inevitably be missing from the list; What I learn can only be applied to the group I am studying.

Question 33

Lecture 7: #11 Describe simple random sampling and list a reason why it is seldom used.

Answer 33

Assigning everyone a number in your population and using computer programs to generate random numbers to eliminate bias.
Seldom used because it is hard to access an entire population.