In order to examine the causal effects of an independent variable on a dependent variable certain manipulations need to be tries. Manipulations simply mean that we create different kinds levels of the independent variables to assess the impact on the dependent variable. For example we may want to test the theory that depth of knowledge of various manufacturing technologies is caused by rotating the employees on all the jobs on the production line and in the design department over a 4 week period. Then we can manipulate the independent variable.
Lets us look at an example on how causal relationships are established by manipulating the independent variable. Let us say we want to test the effects of lighting on worker production levels among sewing machine operators. To establish cause-and-effect relationship we must first measure the production levels of all the operators over 1-15 day period with the usual amount of light they work with say 60 watt lamps. We might then want to split the group of 60 operators with say 60 watt lamps. We might then want to split the group of 60 operators into three groups of 20 members each and while allowing one subgroup to continue to work under the same conditions.
Lets us look at an example on how causal relationships are established by manipulating the independent variable. Let us say we want to test the effects of lighting on worker production levels among sewing machine operators. To establish cause-and-effect relationship we must first measure the production levels of all the operators over 1-15 day period with the usual amount of light they work with say 60 watt lamps. We might then want to split the group of 60 operators with say 60 watt lamps. We might then want to split the group of 60 operators into three groups of 20 members each and while allowing one subgroup to continue to work under the same conditions.
