Chapter 2: Methods & Staticstics in I/O psychology

Question 1

Science is

Answer 1

An approach that involves the understanding, prediction and control of some phenomenon of interst.

Question 2

Psychology is

Answer 2

Understanding, prediction and control of human behavior

W&O-psychology in work-related context

Question 3

Emperical evidence

Answer 3

A data-driven aproach to test theories and relationships

Question 4

Characteristics of “Good”Science, are;

Answer 4

• Logical approach, based on theories from which testable hypotheses can be derived.
• Knowledge based on data.
• Open, transparent, publicly available.
• The process of falsifiability: the inheren possiblitiy that a hypothesis can be proved false.
• Research should be independent and objective concerning their research results.

Question 5

Characteristics of “good” theories, are;

Answer 5

• Are seen as important by the scientific community.
• Peer-reviewed.
• Emperically tested.
• Are verifiable and replicable.

Question 6

Theory is

Answer 6

A set of interrelated concepts, definitions, and propositions that are advanced to explain or predict phenomena.

Question 7

What is the Emperical cycle?

Answer 7

From observation(s), you induce you specific to a general rule, which is a theory or model. Based on that, you can make a deduction going from general to specific, by making a prediction. Testing the preduction, will translate to results. Based on the evaluation, you will make a decision.

Question 8

What are some decisions you make when desigining a research?

Answer 8

• Labatory or fied?
• Participants?
• Conditions and how to assign people to the different experimental conditions?
• What are the relevant variables?
• How to measure the variables?

Question 9

What are the different types of research designs in WO-psychology?

Answer 9

• Experimental.
• Quasi-experimetal
• Non-experimental

Question 10

Experimental

Answer 10

• The Golden standard; allows you to oversee the causal relationships.
• Random assignment of conditions (example: intervention yes/no).

Question 11

Experiments are

Answer 11

• Are studies in which the researcher manipulates a variable in order to observe how it affects another variable that is being studied.
• Experiments provide insight into cause-and-effect by demonstrating what outcome occurs when a particula factor is manipulated.

Question 12

Quasi-experimental:

Answer 12

• Assignment to conditions but not random.

Question 13

Non-experimental

Answer 13

• No assignment to conditions.
• No intervention.

field research (survey) is a non-experimental design.

Question 14

What is the difference between random and non-random sampeling?

Answer 14

There are systemetic factors that you maybe oversee, within the non random assignment of participants. With random assignment you try to hold everything continieus.

Question 15

What are different types of data collection?

Answer 15

• Qualitative research
• Quantitative research
• Triangulation

Question 16

Qualitative research

Answer 16

• For example observation, interviews, case- and diary studies.
• Results are descriptive

Descriptive statistics refer to a set of methods used to summarize and describe the main features of a dataset, such as its central tendency, variability, and distrivution.

Question 17

Quantitative research

Answer 17

• For example test, questionnaires, fysiological measurement.
• Results are numerical

A data type expressed in numbers, rather than natural language description.

Question 18

Triangulation

Answer 18

Converging evidence; testing the same hypothesis by using multiple, different methods.

Question 19

What is the different between independent and dependent variables in an experiment?

Answer 19

• The independent variable is the variable that is varied or manipulated by the researcher.
• The dependent varialbe is the response that is measured.

Question 20

Generability

Answer 20

Capability of being generated.

Question 21

External validity

Answer 21

The degree that the results of one study can be applied to different…
- GROUPS
- Situations/tasks
- time
- organizations

Question 22

What are the different data-analysis?

Answer 22

• Descriptive statistics; central tendency, variability/spread, distirubtion
• Inferential statistics

Question 23

Descriptive statistics

Answer 23

Statistics that summarize, organize, and describe a sample of data.

Question 24

Inferential statistics

Answer 24

Statistics used to aid the researcher in testing hypotheses and making inferences from the sampel to population.

Question 25

Measures of centrale tendency;

Answer 25

• Mean: Average (sum of all scores divided by the sample size).
• Mode: Most common or frequent score in the distribution.
• Median: Middle score, value separating the higher half from the lower half.

111112223334445; mean=2.47. mode=1, median= 2 (whent it was 12345678, the mean is 4.5)

Question 26

Variability/Spread

Answer 26

The extent to which scores in a distirubiton vary; variance, standard deviation.

SD provides information on the proportin of observations above or below certain values.

Question 27

Distribution

Answer 27

Skewness;
- Positive (right).
- Negative (left)

Question 28

No skewness

Answer 28

Distirubiton has bell curve shape, and the mean, median& mode are identical.

Question 29

Positive skewness

Answer 29

Mean, median, and mode are not identical. Most observation to the left of the mean.

Question 30

Normal Distribution

Answer 30

Is the assumption for most statistical technipuqes. Characteristics are:
- Symmetrical.
- Mode=Median=Mean
- About 2/3 of all socres fall between -1SD and +1SD

Question 31

Inferential statistics

Answer 31

Statistics used to test hypotheses and making inferences from the sample to a larger population.
- Differences between groups.
- Strength of association between (two or more) variables.

Question 32

Statistical significance

Answer 32

• Indicates the probability of getting the observed data, assuming the null-hypothesis is true ~Daniel Lakens.
• Null-hypothesis states that there is no effect.

Question 33

Statistical power

Answer 33

• The likelihood of finding a statistically significance difference.
• Power decreases with smaller samples

Question 34

Correlation

Relationship between variables

Answer 34

Inidicates the magnitude and direction of an relationship between two variables, about a linear relationship

Can vary between -1 and +1

Question 35

Correlation NOT Causality

Answer 35

Based on the correlations, you generally can’t conclude that there is a causal relationship between the variables.

Question 36

What are two imporatnat criteria when evaluating measurement instruments?

Answer 36

• Reliability: consistency or stability of a measure.
• Validity: Does the instrument actualy measure what is the supposed to measure?

Question 37

Types of reliability

Answer 37

• Test-retest reliability: measures the consistency of results when you repeat the same test on the same sample at a different point of time.
• Equivalent test reliability: The extent to which measurements on two or more forms of a test is consistent.
• Inter-rater: measurement of the extent to which data collectors (raters) assign the same score to the same variable.
• Internal consistency: A measure of how well a test addresses different constructs and delivers reliable scores.

Question 38

Types of validity

Answer 38

• Content-related validity: Evaluates how well and instrument (like a test) covers all relevant parts of the construct it aims to measure.
• Criterion-related validity: Evaluates how accurately a test measures the outcome it was designed to measure. Predictive (future) and Concurrent (current).
• Construct-related validity; The extent to which you test or measure accurately assesses what it’s supposed to.