Module 2 -1 Practice Questions

Front

What does a correlation coefficient of .957 indicate?

Back

A strong positive relationship between the independent and dependent variables, meaning as the independent variable increases, the dependent variable also increases.

Front

What type of study is it when determining if a characteristic (like handedness) affects an outcome (like lifespan)?

Back

This is an example of a case C -> Q study, where a characteristic (C) is examined for its effect on a quantitative outcome (Q).

Front

How can a relationship be described if it shows a strong curvilinear pattern?

Back

A strong curvilinear relationship indicates that as one variable increases, the other variable changes in a non-linear manner, often following a curve.

Front

Define correlation coefficient.

Back

A statistical measure that describes the strength and direction of a relationship between two variables, ranging from -1 to +1.

Front

What does a correlation coefficient of 0 indicate?

Back

No relationship between the independent and dependent variables.

Front

Explain the difference between case C -> Q and case Q -> C.

Back

Case C -> Q examines how a characteristic affects a quantitative outcome, while case Q -> C looks at how a quantitative outcome influences a characteristic.

Front

What is a strong linear relationship?

Back

A strong linear relationship means that the data points closely follow a straight line, indicating a consistent increase or decrease between the variables.

Front

What is a weak curvilinear relationship?

Back

A weak curvilinear relationship indicates that while there is a non-linear pattern, the data points do not closely follow a curve, showing less consistency.

Front

What is the significance of a p-value in hypothesis testing?

Back

A p-value indicates the probability of obtaining the observed results, or more extreme results, if the null hypothesis is true. A low p-value suggests rejecting the null hypothesis.

Front

Define independent variable.

Back

An independent variable is the variable that is manipulated or changed in an experiment to observe its effect on the dependent variable.