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Systematic observation by nature is structured. Unlike unstructured observation, systematic observation includes recording the phenomenon of interest (i.e. behavior) across different settings and over a significant period of time. The results from such an activity leads to the gathering of meaningful data. This in essence means that the observer can interpret the data to explain and reveal specific patterns of behaviors. Researchers always form hypothesis before entering the field to record events or behaviors, so it is of paramount importance for observers to use a theoretical model to help guide the interpretation of the recorded behaviors or events. Unstructured random observation, in contrast, does not allow anyone to make meaningful interpretations or find meaningful patterns of behaviors.

As for experiments, they are the most important tool that scientists use to produce new knowledge. Experiments involve the manipulation of variables (anything that can take different values). Perhaps the most important feature of experiments is the presence of a control group used for comparison reasons against the experimental group. The control group and the experimental group are identical in every respect, but differ only on the independent variable which is of course the variable the experimenter manipulates. This way, any recorded differences between the two groups could be attributed to the independent variable and not some other confounding variable. Through experiments, researcher can identify causal relations, that is, what causes what. This is the only method that could be used to determine causation in most scientific disciplines.

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Q: Why are systematic observations or experiments are important?
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