An experimenter wants to find out if drinking coffee makes people more alert. The amount of coffee a person drinks is the:

hypothesis.
dependent variable.
independent variable.
correlation coefficient.

Im between A and B.

I think it's the hypothesis

It's one of the variables, but I'm not sure which.

An independent variable is the potential stimulus or cause, usually directly manipulated by the experimenter, so it could also be called a manipulative variable.

A dependent variable is the response or measure of results.

The hypothesis is the statement about how you think the experiment will turn out. For example:

Ho: Coffee has no effect.
Ha: Coffee makes people more alert.

A correlation coefficient is a number, varying between -1 and +1, indicating the degree of relationship between two variables.

I hope this will help you make decisions on this question and others.

In this scenario, the amount of coffee a person drinks is the independent variable. The experimenter is interested in investigating whether drinking coffee has an effect on people's alertness. The independent variable is the factor that the experimenter deliberately manipulates or controls to see if it has an impact on the dependent variable.

The dependent variable, on the other hand, is the outcome or response that the experimenter measures to see if it changes as a result of manipulating the independent variable. In this case, the dependent variable would be the level of alertness of the individuals.

To test the hypothesis that drinking coffee makes people more alert, the experimenter would need to design an experiment where they manipulate the independent variable (amount of coffee consumed) and measure the dependent variable (level of alertness). They could have a control group that does not consume any coffee and an experimental group that consumes varying amounts of coffee, and then compare the levels of alertness between the two groups.

The correlation coefficient, on the other hand, is a statistical measure that quantifies the relationship between two variables. It is not directly related to distinguishing the independent variable or dependent variable in this scenario.