unequivocal means "having only one possible meaning or interpretation, unambiguous, clear." I will be using some college vocabulary in this tutorial that you may not be familiar with so I will give the definition and maybe a short discussion since one of the reasons you are in college is to learn to think and talk like an educated person. When an experiment's outcome only has one possible cause the study's conclusion is unequivocal. On the other hand when there is more than one possible conclusion from a study it is:
equivocal, meaning "allowing the possibility of more than one meaning or interpretation, ambiguous, of dubious character, questionable, dubious, suspicious, not determined." 

In psychology we have one type of study, true experiments, where conclusions from the data are unequivocal since there is only one explanation for the data. When we do an experiment where restaurant servers randomly either introduce themselves by name or don't introduce themselves to diners and the diners who received the name introduction leave a larger average tip (23%) compared to the diners who did not receive the name introduction tip average (15%) the experimenter can unequivocally say, "Name introductions causes higher tips." That is the only explanation for this data. In Osborn's makeup study, when the women were rated as more attractive when wearing makeup than when not, he could unequivocally say, " Makeup causes higher attractiveness ratings." This is justified since the participants had been randomly assigned to see the woman with or without makeup in a true experiment..

Besides true experiments the other type of study done by psychologists (also very common in sociology and political science) are survey studies. These studies are sometimes called correlational studies since the participants are not randomly assigned to the conditions of the independent variables. Explanations for the data from this type of study are equivocal since there may be alternative explanations for the data. Say a researcher does a correlational study where he classifies people into a group of those who are frequent tea drinkers and compares them to a group of non-tea drinkers on their health problems and find the frequent tea drinkers have fewer health problems. Then the researcher says, "Tea drinking causes fewer health problems." HA! you may think, applying critical thinking, since you can see this is an equivocal statement. There are a variety of other explanations for why the tea drinkers may report fewer health problems. To give a simple example, maybe the tea drinkers smoke less and that is the reason they have fewer health problems so the tea just goes along with non-smoking, tea does not cause fewer health problems. (Actually, using special statistical techniques to figure out the relative importance of different factors when you  are studying some characteristic that has multiple causation like health, researchers think that tea does have some positive effect on health.)

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(If you want to think a little more deeply about this)
There is only one little complication in this system. We have been discussing straightforward examples talking about. "Did the condition the experimenter identified (e.g. name versus no-name introduction; makeup versus no-makeup) lead to the outcome, the dependent variable difference (e.g. in tipping; in attractiveness ratings)?" In those examples the superior inferential clarity of an experiment over a correlational study like the tea studies is clear.
 

The other conclusion an experimenter may want to reach from his or her study is how it confirms or disconfirms a theory. For example, Osborn claimed that the fact that makeup increased attractiveness ratings confirmed beauty is a "social construction, a socially given, impression-managed personal identity" and disconfirmed the view beauty is a biological trait (since the woman's biological structure was the same in the makeup and no-makeup conditions there should only have been minor differences in the ratings if beauty is a purely biological trait). While experiments are strong in showing the independent variable caused the dependent variable, there are always disputes about what the experiment means for supporting or disconfirming a theory. In disputing Osborn's theoretical interpretation some have said that makeup has its effect by enabling the madeup woman to simulate biological beauty by disguising imperfections, wrinkles, thereby looking artificially healthy and thus beautiful. Osborn replied, "The problem with this interpretation is, if true, then makeup would be a stealth strategy where the makeup user would want others to not know she was wearing makeup whereas most makeup is obvious, a sign the woman wants to be regarded as beautiful."

So the conclusion is, while experiments are inferentially strong for causal judgments within the experiment, both experiments and correlational studies have debatable implications for theory confirmation. This shows why replication is so important for science since it is by comparing the results from a multitude of studies on one topic that the strengths and weaknesses of competing theories become clear.