Matakuliah : D0064 - Sosiologi dan Psikologi Industri
Tahun : Sep-2009
Pertemuan 05 - 06

• Every study begins with a research question
• Research question can be general or specific
“What causes people to like or dislike their jobs?”  general
• To be useful the question should specify exactly what is being studied. A better question that is more specific is:
“Does level of pay effect how much people like their jobs?  specific
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VARIABLES :
The basic building blocks of a design. A variable is an ATTRIBUTE of characteristic of people or things that can vary (take on different value)
Common variables in organization research :
People’s ability: intelligence
Attitude: job satisfaction
Behavior: absence from work
Job performance: weekly sales
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Variebles are quantified so that they can be analyzed with STATISTICAL METHODS
Independent Variables : manipulated by researchers
Dependent Variables : variables are those assessed in response to the independent variables
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• Random assignment : occurs when people are assigned to various treatment conditions or levels of an independent variables in a non-systematic way  every subject has an equal chance of being assigned to every condition.
• Random assignment is used as a means of control by which groups of subjects can be made more of less equivalent to one another on variables not being studied.
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• Random selection : we choose the subjects of our investigation by a non-systematic method: every possible subject of our study has an equal chance of being chosen to participate.
• Random selection is important if we wish to draw accurate conclusions about the entire group of interest.
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Research design: the basic structure of a scientific study.
Experiment:
Survey Design:
Observation Design:
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• Measurement: the process of assigning numbers to characteristics of people or things.
• Variables in every study must be measured or quantified so that data analysis can be conducted to draw conclusions.
• One of the most critical steps in planning a research study is: DECIDING HOW each variable will be MEASURED .
• Measurement can be classified as either
CATEGORICAL or CONTINUOUS
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CONTINUOUS measurement is used when the numbers represent the amount of the characteristic in questions. Higher number represent more of the characteristic than lower number, so that inferences can be made based on the value of a variable
 Are you hapy? (3) very happy – (2) happy – (1) not happy
CATEGORICAL measurement: when the numbers DO
NOT represent an underlying characteristic than can be measured continuously
 You received the information from: (1) books – (2) friends – (3) media
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Reliability : the consistency of measurement across repeated observations of a variable of the same subject
As the error component increases , observations will DIFFER each time the subject is assessed.
Internal Consistency Reliability:
Test-Retest Reliability:
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Both internal & Test-retest reliability are necessary properties for a useful measuring device.
If a measure contains too much error, it will not give sufficiently accurate measurement to be useful
Reliability is NOT ENOUGH : just because a measuring device is consistent does not mean that it actually assesses the variable of interest
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Validity: represents the true score component
 the inferences made about a measuring device rather thatn the device itself
 An intelligence test is considered valid if people who score high do better than people who score low on tasks that in theory require intelligence
Construct Validity : we are able to give an interpretation to scores on a measure. To say that a measure has construct validity is to say that we have CONFIDENCE in our interpretation of what that measure represents.
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Face Validity : means that a measure appears to assess what it was designed to assess.
Content Validity : means that a multiple item measure of a variable does an adequate of covering the entire domain of the variable.
 a single question would generally be inadequate to cover all the material in an entire chapter of a text book.
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Construct Validity : we are able to give an interpretation to scores on a measure. To say that a measure has construct validity is to say that we have CONFIDENCE in our interpretation of what that measure represents.
Face Validity : means that a measure appears to assess what it was designed to assess.
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Content Validity : means that a multiple item measure of a variable does an adequate of covering the entire domain of the variable.
 a single question would generally be inadequate to cover all the material in an entire chapter of a text book.
Criterion-related validity : means that score on a measure of interest relate to other measures that they should relate to in theory.
Face, Content, Criterion-related validity represents ways to assess validity.
Construct validity is inferred based on research evidence. It is our best guess about what a measure represents.
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Descriptive statistics summarize the results of a study.
* Measure of Central Tendency and Dispersion
* Correlation
* Regresssion
Inferential statistics help interpret the results using a variety of statistical tests.
 Procedures that help you decide if the results can be attributed to | error variance or the experimental treatment
If the probability of finding the mean difference by chance is less than 1 in 20 (0.05), the conclusion is reached. 
Statistical Significance
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Independent Group t test to determine if 2 groups of subjects differ significantly on a dependent variable.
Analysis of Variance ( ANOVA ) to determine if 2 or more groups of subjects differ significantly on a dependent variable
Factorial ANOVA to determine the significance of effects of 2 or more independent variables on a dependent variable
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t test for Correlation to determine if the correlation between 2 variables is significantly greater than zero
Multiple Regression to determine if 2 or more predictor variables can significantly predict a criterion variable
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A single study is never considered o offer a definitive answer to a research question
To achiever confidence about a phenomenon of interest, we need to conduct several studies.
A META-ANALYSIS : a quantitative way of combining results of studies, much like our statistics summarize the results across individual subjects
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A Meta-Analysis can summarize statistically the results of different studies in the domain of interest to I/O Researcher. Such analysis can be simple descriptive summaries of results or very complex mathematical and statistical procedures.
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For example:
Suppose you found 5 studies that reported the following correlation between job satisfaction and pay level:.20, .22, .24, .26, .28
A simple meta-analysis of these 5 studies would conclude that the mean correlation between these 2 variables was .24
In most areas that have been frequently studied, meta-analysis can be found to help interpret what those individual studies have found.
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The researcher must protect the well-being of subjects.
 this means that manipulations, such as an experimental training procedures, should be used if they are known to cause harm
The researchers must take care to PROTECT
IDENTITIES when appropriate
It would be considered unethical to violate confidentiality and disclose the identities of surveyed employees.
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The well-being of individuals against the wellbeing of organization has to be weighted carefully
An ethical psychologist will discuss the issue with other psychologists and with superiors in the hope of reaching an ethical and satisfactory decision.
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It is good idea to try to foresee these situations and avoid them. If you suspect that supervisors might demand to know employee identities, conduct surveys anonymously. If you do not know the identities, you cannot disclose them.
If there is even a slight possibility that there can be some drawbacks to participation, the person should be asked to sign an informed consent form .
These forms explain the nature of a study and what is expected of the subject.
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