4: Research Methods 2

Question 1

When do you use Case studies? How do they work? What do they provide?

Answer 1

• We use case studies when we have very rare disorders/diseases
• Case studies conduct in-depth interviews to gain insight into a rare disorder
• Case studies can provide profound insight into the workings of the brain

Question 2

Name some examples of groups that are used as case studies:

Answer 2

Hyperthymia- incredible autobiographical memory: 60 people in the world have it

conjoined twins- twins but conjoined

When COVID-19 started- case studies into the disease and treatment

Question 3

What are the pros and cons for case studies?

Answer 3

Pros
- provide incredible detail on what’s being studied
Cons
- The cases are often of rare disorders, so the application off knowledge is limited

Question 4

Why do you use naturalistic observation? What do you have to consider when doing naturalistic observation?

Answer 4

Some behaviors are not socially acceptable, so results can be skewed.
You have to be inconspicuous so that you don’t alert people (they’ll change their behavior).

Question 5

What are the pros and cons of naturalistic observation? How can we bypass some of these cons?

Answer 5

Pros
- very high on ecological validity - findings=generalizable
cons
- difficult to set up (what if nobody shows up?)
- Observer bias - researchers seeing what they want to see. Get around this by having multiple people watching the same behavior and compare notes.

Question 6

What are surveys? What can they do?

Answer 6

Surveys are lists of questions answered by research participants.
They allow people to gage public understanding /
interest in something.

Question 7

What are the pros and cons to surveys?

Answer 7

Pros
- very large sample size
- better generalization to the population
Cons
- Sacrifice richness of data / not as in-depth as case studies
- doesn’t provide a lot of explanation for the results
- people could lie/misremember

Question 8

how does Archival Research work?

Answer 8

Archival research relies on looking at past records or data sets to look for interesting patterns or relationships

Question 9

What are the pros and cons to archival Research?

Answer 9

Pros
- the researcher employing archival research never directly interests with research participants, so low investment of time and money
Cons
- Questions must be tailored so that they can be answered using existing data sets
- no guarantee of consistency between records from different sources, so might make comparing/contrasting data a problem

Question 10

How do longitudinal and Cross-sectional Research work?

Answer 10

Longitudinal research gathers data over a very long time period. Ex/ Surveying a group of people every 10 years for 20 years (20, 30, 40).

Cross-sectional research tries to understand and sort out the differences between 2 or more sets of data (variables) . Ex/ Surveying a group of 20 year-olds, comparing them to a group of 30 year-olds and 40-year-olds at the SAME TIME.

Question 11

What are the pros and cons of Longitudinal research?

Answer 11

Pros
- provides a better understanding between the relationship of cause and effect.
- Lets you see how processes unfold over time (how friendships are build, unfold, evolve, etc.)
Cons
- Very time and money intensive
- Participants can drop out
- 3rd variable problem

Question 12

What are the pros and cons of Cross-sectional research?

Answer 12

Pros
- cross-sectional research requires a shorter-term investment than longitudinal research
Cons
- Results are limited by differences that exist between the different generations (or cohorts) that have nothing to do with age.

Question 13

What is covariation, and how do you know that we subconsciously know about this?

Answer 13

Covariation refers to the fact that we subconsciously want to find the relationship between 2 variables, especially cause and effect relationships.
Ex/ We experimented with “not coming to school” and we’ve seen the “outcome”

Question 14

What are the three general types of correlations?

Answer 14

Positive correlation
- positive x, positive y : Did you get enough sleep last night + Did you sleep well.
Negative Correlation
- positive x, negative y : Did you sleep well + How tired are you?
No Relationship
- x and y are completely unrelated

Question 15

Generally, what is a small, medium, and large correlation coefficient?

Answer 15

0.1 is small
0.3 is medium
0.5 is large
values set arbitrarily

Question 16

What do correlation coefficients do? What do they show? What can you do with them?

Answer 16

Correlation coefficients can quantify a relationship between 2 variables
They can show the direction of said relationship (+/-)
Correlation coefficients are also directly comparable

Question 17

What do you have to keep in mind about correlations?

Answer 17

Correlation does not “imply” causation.
Ex/ There is a correlation between close friends + happiness, but that doesn’t mean that that one causes the other.
Do friendships cause happiness, or do happier people make close friends more easily?

Question 18

What is a confounding variable?

Answer 18

A confounding variable is a third variable in a correlation that can affect the relationships between the first 2. It can make it seem like there is a cause and effect relationship happening when there isn’t.

Ex/ Head size and intelligence seem like they’re part of a cause and effect correlation, but upon further analysis, the confounding/third variable of “social economic status” can be found linking the first 2 variables together.

Question 19

What are illusory correlations?

Answer 19

Illusory correlations refer to when two things correlate by change (1 in 20)

Ex/ Number of people drowned by falling in a pool ~ Nicholas Cage films: r = 66 (which is really freaking high!)

Question 20

How do correlations relate to research design?

Answer 20

If we measure a correlation between variables at one point in time, then it’s cross-sectional

Question 21

What is a correlation/ what does correlation mean?

Answer 21

Correlation means that there is a relationship between two or more variables (such as ice cream consumption and crime), but this relationship does not necessarily imply cause and effect. When two variables are correlated, it simply means that as one variable changes, so does the other.