Week 2: Research Methods

Question 1

Key Elements of a Statistical Investigation

Answer 1

1. Planning the Study
   - Testable research question
2. Examining the data
   - Graphs and descriptive statistic to summarize data
3. Inferring from the data
   - Apply statistical methods. ex ANOVA test
4. Drawing conclusions
   Causal Conclusion - the variable cause the effect
   Associational Conclusions - the two variables are correlated but not necessarily causal

Question 2

Distribution

Answer 2

Pattern of variation

Question 3

Significance

Answer 3

Result is statistically significant if it is unlikely to arise by chance alone

Question 4

Random Sampling

Answer 4

• gives every member of the population a equal chance of being selected
• Accounts for confounding variables

Question 5

Margin of Error

Answer 5

Expect amount of random variation in a statistic (95% confidence level)

Question 6

Internal Validity

Answer 6

Degree to which a cause-effect relationship between two variables has been unambiguously established

Question 7

External Validity

Answer 7

Degree to which the findings of a specific sample can be generalized to a larger population

Question 8

Ecological Validity

Answer 8

Degree to which a study finding has been obtained under real life conditions

Question 9

Experience-Sampling Method

Answer 9

Participants report on their momentary thoughts, feeling, and behaviours at different points in time over the course of a day

Question 10

Ecological Momentary Assessment

Answer 10

Methodologies that repeatedly sample participants’ real work experiences, behaviour and physiology in real time

Question 11

Diary Method

Answer 11

Participants complete a questionnaire about their thoughts, feelings and behaviour of the day each night

Question 12

Day Reconstruction Method (DRM)

Answer 12

A methodology where participants describe their experiences and behaviour of a given day by systematically reconstructing it the following day.

Question 13

Correlational Studies

Answer 13

• Researcher does not manipulate any variables, they record existing values
• Determine the association of two variables but can’t tell which one causes the other
• Allows us to study topics we can’t experimentally manipulate. ex. income

Question 14

Correlation

Answer 14

Measures the association between two variables

Question 15

Experimental Research

Answer 15

Manipulation of independent variable and measures effect on a dependent variable
Random Assignment:
- removes confounding influences
- use double blind procedure to limit confounds
Strength: has causality and interval validity
Weak: lacks ecological validity

Question 15

Confounding Variables

Answer 15

Placebo Effect - Change in behaviour because they believe they are receiving treatment
Participant Demand - Participants behave how they think the experimenter want
Experimenter Expectations - biases in observations

Question 16

Participant Observation

Answer 16

Research embeds themselves in the group or setting to observe behaviours, interactions, and dynamics
Overt - know being observed
Covert - don’t know being observed

Question 17

Case Study

Answer 17

In depth examination of specific individual or contexts
- extensive rounds of testing
- limited number of participant based on inclusion criteria
Weakness: Generalization external validity

Question 18

Narrative Analysis

Answer 18

• Studying personal accounts, stories and how they’re told
• Analysis of speech
• Stories may be written, audio recorded or video recorded
  Weakness: external validity and researcher bias

Question 19

Quasi Experimental Designs

Answer 19

Like experiments but without random assignment
- Assignment to conditions based on pre-existing ingroups
- The conditions are the independent variables
Weakness: lacks causality because confounding variables

Question 20

Longitudinal Studies

Answer 20

Track the same participants over time

Question 21

Surveys

Answer 21

Collect self reported data via questionnaires
- Larger sample size at lower cost