Two Variable Statistics

Front

What is the meaning of the slope in a linear relationship?

Back

The slope represents the number of hours needed to study to attain a certain grade.

Front

How can you determine the number of hours a student should study to achieve a specific grade using the Line of Best Fit?

Back

You can use the Line of Best Fit to estimate that a student should study approximately 6.9 hours to make an 80 on the final exam.

Front

What does a strong positive correlation indicate about the data?

Back

A strong positive correlation indicates that as one variable increases, the other variable also tends to increase.

Front

What is the correlation coefficient for a Best Fit Linear model?

Back

The correlation coefficient for a Best Fit Linear model is a measure of how well the data fits the line, with values close to 1 indicating a strong relationship.

Front

What is the correlation coefficient?

Back

The correlation coefficient quantifies the strength and direction of a relationship between two variables, with values ranging from -1 to 1.

Front

What does a correlation coefficient of 0.97 indicate?

Back

A correlation coefficient of 0.97 indicates a very strong positive linear relationship between the two variables.

Front

What does a correlation coefficient of 0.94 suggest about the data?

Back

A correlation coefficient of 0.94 suggests a strong positive relationship, meaning that as one variable increases, the other variable also tends to increase.

Front

What is the purpose of the Line of Best Fit in statistics?

Back

The Line of Best Fit is used to summarize the relationship between two variables and to make predictions based on that relationship.

Front

How do you interpret a slope of 2 in a study hours vs. grade relationship?

Back

A slope of 2 means that for every additional hour studied, the grade increases by 2 points.

Front

What is the significance of a negative correlation coefficient?

Back

A negative correlation coefficient indicates that as one variable increases, the other variable tends to decrease.