Statistics Lesson 1 - Introduction to statistics.ppt

Also known as mediator variable example the

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Also known as Mediator Variable.
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Example: The researcher found out that during students’ enrollment period the manual information system makes the personnel in- charge inefficient. Independent: Manual Information System Experiment Unit: personnel in-charge Dependent : Efficiency (Measurable)= Inefficient (low assessment result) Intervening : Why the relationship of Manual Information System and Inefficiency exist? Due to students’ enrollment period
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Moderator Variables It is a third variable that affects the strength of the relationship between a dependent and independent variable in correlation.
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Example The researcher found out that a manual information system is prone to human error which makes personnel in-charge inefficient while using a computerized system that has self data validation capability makes a personnel in-charge efficient during students’ enrollment period. Independent: Manual Information System Experiment Unit: personnel in-charge Dependent : Efficiency (Measurable)= Inefficient (low assessment result) Intervening : Why the relationship of Manual Information System and Inefficiency exist? students’ enrollment period Moderator Variable: prone to human-error >Manual Information System > inefficient > personnel in-charge Has self data validation > Computerized Information System > Efficient > personnel in-charge
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Extraneous Variable These are variable that you are not intentionally studying in your experiment or test. When you run an experiment, you’re looking to see if one variable has an effect on another variable.
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Types of extraneous variable Demand characteristics Experimenter / Investigator effects Participant Variables Situational Variables
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Demand Characteristics environmental clues which tell the participant how to behave, like features in the surrounding or researcher’s non- verbal behavior.
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Investigator Effects where the researcher unintentionally affects the outcome by giving clues to the participants about how they should behave.
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Participant Variables like prior knowledge, health status or any other individual characteristic that could affect the outcome.
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Situational Variables Situational like noise, lighting or temperature in environment.
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