CH. 2 Flashcards

1
Q

Three Goals of Science

A

Describe
- Take a photograph of the state of events. How are things currently?
Means, variance, correlations, percentages, frequencies
- Predict
Based on past observed patterns, who do we think will do well in this job?
Take correlations (and regressions) from one sample in which we KNOW the answer and apply the numbers to a new sample in which we don’t
- Explain
Most difficult—why did Sally have the highest sales last year? What’s her secret?
Seeks a causal answer to what happened
Requires scientists to form a theory and test that theory in an experiment (to rule out other possible explanations).
Usually compare group with t-tests, F-tests, or regression

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2
Q

The Empirical Research Process

A
  • Statement of the Problem
  • Design of research study
  • Measurement of variables
  • Analysis of data
  • Conclusion from research
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3
Q

Statement of the Problem: What is a Theory?

A
  • A statement that proposes to explain relationships among phenomena

Example: Attractive people are more likely to get a job than unattractive people

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4
Q

Inductive vs. deductive method

A

Theory comes first in deductive method
Form a theory, test that theory
Data come first in inductive method
Gather data, form a conclusion based on that data

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5
Q

Why is Theory important and why might it not be necessary? Ups and Downs?

A

Why theory is important in psychology
- Integrates and summarizes past research and provides a framework for new research
Reduces the tendency toward Type I error (saying you found something that doesn’t actually exists)

Why theory may not be necessary (or at least not always)
- People can miss important findings if they are only looking where they’re looking (become blinded by their theories)

If we never did exploratory analyses, how would counterintuitive (unexpected) findings be found?
- A lot of effort is expended forming theories that may not be supported or will eventually fall out of favor
Productive research does not require a theory

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6
Q

Internal vs. external validity

A

Research design
- A plan for conducting a study
Choice of design depends on the nature of the problem being studied (and cost and feasibility)

Trade-off between internal and external validity
- The more controlled the experiment is (the more you control for potential third variables or confounds) the more internal validity you have
The more natural the setting, the more external validity you have
- The more likely it is that the results in your study are representative of what would happen in the real world (how generalizable is it to the real world)

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7
Q

Primary Research Methods (PRM)- 4 Parts

1. Laboratory Experiment

A
1. Laboratory Experiment
People come into a highly controlled laboratory setting and get randomly assigned to condition
Can infer causality (more internally valid)
Less generalizable (less externally valid)
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8
Q

PRM - 2. Quasi-Experiment

A

Something about the study is not randomly assigned—maybe you’re comparing men and women or comparing different work groups
You could randomly assign a particular condition, but if another is not randomly assigned, it’s still a quasi-experiment
Book says all field studies quasi-experimental
Less control, more generalizability

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9
Q

PRM - 3.

A

No manipulation—everyone gets the same questions
Response rate problem
Not everyone responds, might decrease generalizability
Truthfulness of responses
For a job, people may want to lie to look good
However, can make surveys anonymous to increase truthfulness
Internet surveys

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10
Q

PRM - 4. Observation

A

Generate ideas for further testing
Rich with data in environment where behavior being studied occurs
BUT your presence could affect behavior

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11
Q

Secondary Research Methods (SRM) - 1. Meta-analysis - Problems with it.

A

Meta-analysis
Statistical study of studies – aggregates results
Estimate of “true” relationship
Subjective decisions have to be made
File drawer effect of non-published studies
Problem from differences in level of analysis of original studies
If one study focuses

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12
Q

SRM - 2. Data Mining

A

“Big Data”

Used to reveal patterns of large data sets

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13
Q

Qualitative data

A
Qualitative data can be collected within the context of any of the contexts mentioned (laboratory, quasi-experimental, questionnaire, observation)
Book says qualitative research is a class of research methods in which the investigator takes an active role in interacting with the subjects he or she wishes to study.
I think qualitative research is anything that is not automatically put into numbers (e.g
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14
Q

Ethnography

A

The art and science of describing a group or culture (e.g., work group or organization)
Researcher tries to keep an open mind but nearly impossible to not have preconceived notions
Tries to be aware of what is the participants’ awareness and experience versus the detached outside investigator
Emic – insider perspective
Etic – outsider perspective
Still rarely used in comparison to quantitative research

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15
Q

Steps 3&4 - Measurement & Analysis: Quantitative

A

Measurement of Variables
- Inherently numerical
Can be continuous (like age, time, speed, and weight)
A “ratio” scale is a continuous scale that has a zero point that means nothing is there (e.g., 0 lbs)
Can be interval
Likert scales (1 = not at all, 7 = Extremely)

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16
Q

Steps 3&4 - Measurement & Analysis: Categorical

A

Not inherently numerical
Variables that can be grouped into categories (experimental conditions, sex, race)
Can be coded into numbers (e.g., 1 = men, 0 = women), but numbers do not inherently mean anything—they represent a category

17
Q

Measurement of Variables – Independent vs. Dependent

A

Usually the terminology used to describe variables within an experimental context
Independent variable = What you manipulate
Dependent variable = What you are interested in

18
Q

Measurement of Variables – Predictor vs. Criterion

A

Measurement of Variables – Predictor vs. Criterion
Unlike IV and DV, predictor and criterion are usually used to describe correlational research (not experimental research)
Typically used to describe data that occurs across time (predictor being first, criterion being second)
High school GPA (predictor) predicts College GPA (criterion)
Conscientiousness (predictor) predicts lower rates of absenteeism (criterion)
OR just theoretically speaking, the researcher forms a hypothesis about which variable came first
Naturally occurring leadership style (predictor) predicts employee performance (criterion)
In this class, we’ll be talking more about predictors and criterions than IVs and DVs

19
Q

Steps 3 & 4: Measurement & Analysis: The Correlation Coefficient, Regression, No Causality

A

The Correlation Coefficient (r)
Reflects degree of linear relationship
Range from -1.00 to + 1.00
Direction is either positive or negative
Magnitude – size is index of strength of the relationship
Remember that -.9 is just as strong of a magnitude as +.9
Regression
Allows you to specify predictor and criterion variables
Allows you to use more than one predictor to predict a criterion variable
Causality cannot be inferred from correlation
Determining causality through non-experimental methods is highly controversial

20
Q

Step 5: Conclusions from Research

A

Factors to consider when speaking to the generalizability of your results
Representativeness of subjects
Degree of fit between subjects and research task
Research method (laboratory vs. field study)
Reminder: Generalizability is the degree to which your results would hold true in other samples and contexts
Research is a cumulative process
No one study can answer all questions
State your limitations and define the scope of your work

21
Q

Ethical Issues in Research

A
APA Code of Ethics – Five rights of participants
Informed consent
Privacy
Confidentiality
Protection from deception
Debriefing
 Employees participating in research are privy to these rights too
No coercion! 
Maintain confidentiality as promised
22
Q

Academic-based and Practitioner-based Research

A

Scientist-practitioner gap
Difference between scientific research findings on organizations and their management versus how organizations are actually managed
Disconnect between academics and practitioners
Descriptive vs. prescriptive information
Correlational findings are largely descriptive (X and Y are related)
Managers want prescriptive findings (If X occurs, do Y)
Lay people always want the bottom line and what they should do whereas researchers are attune (possibly too attune) to the nuances/details