Summary of lectures of 1JP00 - Fundamentals of work and organizational psychology for premasters for the premaster of Innovation Management (Industrial Engineering) at Eindhoven University of Technology.
Chapter 2: methods and statistics in W&O psychology
Science: Understanding, prediction and control of some phenomenon of interest
Psychology: Understanding, prediction and control of human behaviour
Work and organization is science and psychology in work-related context.
Theories are seen as important by scientific community, peer-reviewed, empirically tested, verifiable
and replicable.
Theory development by the empirical cycle:
1) Limited set of observations
2) Generalized statement
3) Theory / model formulation
4) Specific prediction / hypothesis by deduction
5) Testing the prediction
6) Evaluation and updating previous assumption
7) New working theory or model (induction / deduction develops theories)
Designing research decisions:
- Laboratory or field?
- Participants?
- Conditions and how to assign people to the different experimental conditions?
- What are the relevant variables?
- How to measure the variables?
W&O psychology research designs:
1. Experimental – the golden standard, because it allows testing hypotheses on causal
relationships between phenomena. Random assignment to conditions and testing of unknown
relationships
2. Quasi-experimental – assignment to conditions, but not random. Using pre-existing groups as
experimental conditions (e.g., boys vs girls, employees of a company over 3 locations). The
effect/outcome in a quasi-experiment can also be attributed to another systematic difference
between groups.
3. Non-experimental – no assignment to conditions. No intervention, an example could be
survey research, causal claims cannot be made from such a study.
Data collection:
1. Qualitative research – descriptive results
2. Quantitative research – numerical results
3. Triangulation – convergence of evidence through multiple, different methods
Generality: external validity is the degree to which the results of one study can be applied to different
groups / situations / tasks / time / organizations.
, Lecture 2
Data analysis
Descriptive statistics – characterizes something of the population you are interested in (e.g., average
IQ of a population)
Inferential statistics – statistics used to aid the researcher in testing hypotheses and making
interferences (used to make sure that the data you see is not caused by noise, so we can arrive at a
conclusion whether there is a significant difference or not.
Types of descriptive statistics
Measures of central tendency – mean (average), median (middle score), mode (most common score)
Variability – extent to which the scores in a distribution vary (Variance and standard deviation)
Distribution – skewness. Skewness does not address valences; it is just terminology.
- No skewness means a normal distribution (mean, median and mode are identical)
- Positive skewness means that the mean, median and mode are not identical. Most
observations are to the left of the mean.
- Normal distribution – the assumption for most statistical techniques. Characters are that the
distribution is symmetrical, the mean, median and mode are identical and approximately 2/3
of all scores fall between -1SD and +1SD.
Inferential statistics
Inferential statistics are statistics used to test hypotheses and making inferences from the sample to a
larger population. It takes into account differences between groups, and the strength of association
between (2 or more) variables.
Statistical significance is described by the p-value and the null-hypothesis (states that there is no
effect). This refers to the probability of obtaining the observed data assuming the null hypothesis is
true.
Statistical power is the likelihood of finding a statistically significant difference when a true difference
exists. The power decreases when using smaller samples.
Correlation coefficient indicates the magnitude and direction of the relationship between 2 variables
(direction can vary between -1 and +1). The correlation tells you something about the linearity of the
relationship.
Correlation does not equal causation
Criteria for measurement instruments:
1) Reliability (consistency or stability of a measure)
a. Test-retest reliability
b. Equivalent test reliability
c. Inter-rate reliability
2) Validity (does the instrument actually measure what it is supposed to measure?
a. Content-related
b. Criterion-related (predictive or concurrent)
c. Construct-related
Chapter 3: Individual Differences and Assessment
Differential psychology: study of individual differences
Psychometrics: measurement of human capabilities
, Assumptions regarding individual differences:
- Adults have attributes that are relatively stable over time (e.g., personality, intelligence)
- People differ in these attributes
- Differences between people remain the same, even after training, job experiences or other
interventions
- Different jobs require different attributes
- Both job requirements and personal attributes are needed to fit to cause good performance
and effective work behavior
Module 3.2 Human attributes
IQ stands for intelligence quotient. Intelligence is a general mental ability. Carroll (1993) described the
intelligence model:
- Fluid intelligence: understanding things quickly / flexible in reasoning
- Crystallized intelligence: knowledge and experience accumulated over a lifetime
Other human attributes are physical abilities (muscular strength, cardiovascular endurance,
movement quality), sensory abilities (vision, hearing, taste, touch, smell, kinesthetic feedback), or
personality.
Personality: predisposition (typical patterns of behavior, thinking and emotion) – habitual way of
responding.
- Leading Taxonomy / model: five-factor model (FFM) / big five
o Emotional stability / Neuroticism (secure, calm, relaxed)
o Extraversion/Introversion (sociable talkative, energetic)
o Openness to experience (curious, creative, independent)
o Agreeableness (friendly, likeable, cooperative)
o Conscientiousness (responsible, persistent, achievement-oriented)
o Acronym: OCEAN (might be an exam question)
- Personality has an influence on work behaviour independent of cognitive ability
o (cognitive) ability is attributed to knowledge and skills of a person
o Personality is attributed to motivation of a person
- Conscientiousness is crucial
o Most important trait / predictor in work situations
o Bigger impact on work behaviour as the autonomy of employees increases
▪ Where was I half a year ago, and where am I now? What were the rules and
what are they now? What does it say about autonomy and how to deal with
it?
o Personality factors have influence on different jobs:
▪ Emotional stability → security jobs, teamwork
▪ Extraversion → sales performance, management
▪ Openness to experience → expats, success in training
▪ Agreeableness → customer service, teamwork
o Functional personality at work: combinations of personality dimensions/traits predict
success
o Emotional intelligence
▪ “An individual’s ability to perceive emotion in self and others, to understand
emotion, and then to manage emotion in self and others”
▪ Not without criticism: overlap with cognitive ability and with personality (big
five)?
▪ Measurement ‘streams’:
• Ability test
• Self – and peer-report instruments
• Mixed instruments
o Ability & mixed instruments are good measures, report
instruments are not.
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