Yes it depends on what you are measuring in your study. some examples of variable include age, sex, marital status among others
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The independent variable in ANOVA must be categorical (either nominal or ordinal). The dependent variable must be scale (either interval or ratio). However, it is possible to recode scale variables to categorical and vice versa in order to perform ANOVA. While this is a common practice in many social sciences, it is controversial. I have also seen studies where ordinal data is treated as scale in ANOVA. Personally, I do not endorse either practice as they are tailoring the data to fit the test instead of the proper method of selecting a test that fits the data.
A positive correlation between two variables, say X and Y, means that if one increases, the other will too. No correlation means that they are not related. A negative correlation means that as one increases, the other decreases. Normally you will see this in studies as "Recent studies demonstrated a positive correlation between eating too much and obesity." Or, "recent studies demonstrate a negative correlation between a healthy, balanced diet and obesity".
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