Lectures (Midterm I)

Question 1

Confirmation Bias

Answer 1

Noticing supporting evidence and disregarding disconfirming evidence

Question 2

Experimental control

Answer 2

There must be an appropriate control condition in order to avoid confounds

Question 3

Bias

Answer 3

Measurement error in a particular direction - expectancy effects. This is why blind and double blind studies important

Question 4

Reliability

Answer 4

Replicability of a result. High correlation if you retry experiment with same measure. Inter-rater reliability.

Question 5

Validity

Answer 5

How legitimate a measurement is for measuring the thing you want it to. Both internal validity (experimental cohesiveness) and external validity (generalizability) important

Question 6

Internal validity

Answer 6

How cohesive an experiment is - whether it avoids confounding (more than one possible independent variable acting at the same time). Less confounding -> higher internal validity

Question 7

Statistical significance

Answer 7

Unlikely to occur by chance

Question 8

Correlation coefficients

Answer 8

Pearson’s correlation coefficient - “r”

-1 to +1

Question 9

Descriptive statistics

Answer 9

Summarize/describe data: mean, median, mode, etc.

Question 10

Regression analysis

Answer 10

Analysis: how the of the dependent variable changes when any one of the independent variables is varied, while the other independent variables are held fixed.

Question 11

Median split analysis

Answer 11

Dividing the sample in two categories via the median for analysis - can compare means using t-tst

Question 12

Mediator variables

Answer 12

The independent variable influences the (non-observable) mediator variable, which in turn influences the dependent variable.

Question 13

MS vs. MTS

Answer 13

MS measure is multidimensional, MTS is unidimensional. MTS developed because of concerns of problematic questions in MS.

Question 14

t-tests

Answer 14

Look at whether there is significant difference between means of different groups. Can use in median split analysis. Different from correlations, which look at relationships between variables.

Question 15

p-value

Answer 15

How likely are we to obtain the pattern of data by chance? Before p-value test is performed, a threshold (alpha value) of usually 5% is chosen. A small p-value (p

Question 16

Alpha level

Answer 16

Usually set at 5%. If p-value is less than alpha then there is a 5% or less likelihood that could have gotten results indicating relationship if no relationship really present.

Question 17

Operational definition

Answer 17

Defining something according to the process that is used to measure it.

Question 18

Null hypothesis

Answer 18

Default position that there is no relationship between the variables

Question 19

Effect size

Answer 19

How strong the relationship between the variables is

Question 20

Motivated reasoning

Answer 20

Motivation can cause confirmation bias. If hypothesis would be good for you if true, look for positive outcomes and confirmation. If negative, then either more objective or look for disconfirming evidence.

Question 21

Possible reasons for confirmation bias

Answer 21

Reduce cognitive dissonance, ease of processing positives, motivations/meeting goals

Question 22

Dual task paradigm

Answer 22

Two independent variables - a primary task and a secondary task. There may be interactions between the two - a specific condition in one may lead to a specific condition in the other. Adjust parameters in both conditions (2x2) to determine effects. DVs for both the primary and secondary tasks

Question 23

Accuracy

Answer 23

How well a measuring instrument is able to measure - calibration, decimal places, etc.

Question 24

Face validity

Answer 24

Extent to which a test is subjectively viewed as covering the concept it purports to measure.

Question 25

Content validity

Answer 25

Extent to which a measure represents all facets of a given construct.

Question 26

Criterion related validity

Answer 26

Concurrent, predictive: Extent to which a measure is related to an outcome.

Question 27

Construct validity

Answer 27

The degree to which a test measures what it claims, or purports, to be measuring