Week 2 RESEARCH METHODS

Question 1

Key components to a statistical investigation are:

Answer 1

Planning the study: ask testable research question & decide how to collect the data

Examining the data: how? Using what graphs?

Reliability: consistency of measure

Validity: degree to which a measure is assessing what it is intended to measure (how much smth is actually testing what it’s supposed to)

Inferring from the data: draw inferences “beyond” the data

Drawing conclusions: based on what you learned, what can you draw?

Cause and effect conclusion: whether one variables changes the other

Question 2

Distributional thinking

Answer 2

Data varies, so think of meaningful ways to capture that data-

Question 3

Pattern of variation:

Answer 3

the distribution of the data (how variated it is)

Question 4

Statistical significance/Significance:

Answer 4

a result is important only if it is unlikely to be caused by chance but rather science

Question 5

P-value

Answer 5

the amount of probability something might happen (want it to be low, so that it can actually be related to science)

Question 6

Sample: (DEF)

Answer 6

subset of individuals

Question 7

Population: (DEF)

Answer 7

large group of individuals that sample came from and represents

Question 8

Generalized

Answer 8

Conclusions from a sample can be generalized to represent the larger population

Question 9

Random sample: (DEF)

Answer 9

use probability to select subset of people for a sample

Question 10

Margin of error: (DEF)

Answer 10

statistic expressing the amount of random sampling error in the results of a survey

Question 11

Randomly assigning: (DEF)

Answer 11

using probability-based method to divide sample into smaller treatment groups (Balances all variables)

Question 12

Correlational design

Answer 12

▪ When scientists passively observe and measure phenomena

▪ Do not interfere and change behavior.

▪Identify patterns.

Question 13

Positive correlation (scatter plot)

Answer 13

variables move together (inr. slope)
as x incr. y incr.

Question 14

negative correlation (scatter plot)

Answer 14

variables move in opposite directions (dcr. slope)
as x incr. y decr.

Question 15

Strong VS weak correlation

Answer 15

strong: Higher absolute value
weak: if close to 0 variables are unrelated to eachother

Question 16

If correlation found, can you assume there is causation?

Answer 16

NO. CORRELATION =/= CAUSATION
Just because 2 variables have a correlation, can’t say they are caused by one other because don’t know which one came first. perhaps confounding variable present.

Question 17

Experimental design

Answer 17

▪ Researchers measure abstract concepts, like happiness, with operational definitions

▪ Random assignment so participants can choose their conditions

▪ Researchers manipulate independent variable to observe changes in dependent variable

Question 18

Operational definitions: (DEF)

Answer 18

Should be clear, objective, and specific to be tested and quantified

Question 19

Confounding variables: (DEF)

Answer 19

other things that affect influences both IV and DV

Question 20

Examples of cofounding variables

Answer 20

▪ Placebo effect
▪ Experimenter expectations
▪ Participant demand

Question 21

Double-blind procedure: (DEF)

Answer 21

experimenter nor participant knows participant’s conditions

Question 22

Qualitative designs:

Answer 22

Allows to study topics that we cant experimentally manipulate.

Question 23

Observation

Answer 23

often involves researcher embedding self into group- (ex. Wanted to study cult, pretending to be in cult)

Question 24

Case study

Answer 24

examines specific individuals or contexts

Question 25

Narrative analysis

Answer 25

studies stories and personal accounts (analyze themes, structures, and dialogues of these narrative)

Question 26

Quasi- Experimental designs:

Answer 26

▪ does not require random assignment ▪ Subjects assigned to nonrandom groups (e.g. marriages, classes) ▪ Treated as IVs

Question 27

Longitudinal studies

Answer 27

Def: follows same group of individuals over time More precise than a survey but quite costly to conduct

Question 28

Internal validity: (DEF)

Answer 28

make sure results are bc of iv being changed (not biases and not confounds)

Question 29

External validity: (DEF)

Answer 29

make sure results can be applied to other studies (if post results, people can use them to apply to other situations)

Question 30

External or Internal validity? which one more important and why?

Answer 30

Internal

Question 31

Field studies:

Answer 31

doesn't happen in the lab/in the feild

Question 32

Ecological validity: (DEF)

Answer 32

rather than being so controlled (in a lab setting) makes the experiment more natural and day-to-day(being in a lab is so controlled, so less likely to happen in real world)

Question 33

Experience-sampling method: (Studying psychology in the real world)

Answer 33

participants report throughout their day

Question 34

Diary method: (Studying psychology in the real world)

Answer 34

participants report and have questionnaire at the end of their day

Question 35

Electronically activated recorder (EAR): (Studying psychology in the real world)

Answer 35

put something in ur ear to record different parts and understand day-to-day experiences

Question 35

Day reconstruction method (DRM): (Studying psychology in the real world)

Answer 35

obtains info by having participant systematically break down and reflect on prior day, noting feelings/mood changes of distinct events

Question 36

Ambulatory assessments: (Studying psychology in the real world)

Answer 36

EEGs, ECGs, sweat tests, and biomarkers all help study physiology in daily lives

Question 37

Linguistic analyses:

Answer 37

way to extract grammatical and psychological info from a test by counting word frequencies