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The process of replication in an experiment often involves: ensuring that all laboratory animals can reproduce, so that the same experiment can be done on the progeny. repeating an experiment on different units or under different conditions. accounting for the effects of lurking variables by using a matched pairs before and after design. eliminating any interviewer bias present in the experiment. matching pairs on characteristics such as height and randomly assigning each pair member to experiment 1 and experiment 2.

The process of replication in an experiment often involves: ensuring that all laboratory animals can reproduce, so that the same experiment can be done on the progeny. repeating an experiment on different units or under different conditions. accounting for the effects of lurking variables by using a matched pairs before and after design. eliminating any interviewer bias present in the experiment. matching pairs on characteristics such as height and randomly assigning each pair member to experiment 1 and experiment 2.

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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The process of replication in an experiment often involves: ensuring that all laboratory animals can reproduce, so that the same experiment can be done on the progeny. repeating an experiment on different units or under different conditions. accounting for the effects of lurking variables by using a matched pairs before and after design. eliminating any interviewer bias present in the experiment. matching pairs on characteristics such as height and randomly assigning each pair member to experiment 1 and experiment 2.
Transcribed Image Text:The process of replication in an experiment often involves: ensuring that all laboratory animals can reproduce, so that the same experiment can be done on the progeny. repeating an experiment on different units or under different conditions. accounting for the effects of lurking variables by using a matched pairs before and after design. eliminating any interviewer bias present in the experiment. matching pairs on characteristics such as height and randomly assigning each pair member to experiment 1 and experiment 2.
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