Two Way Tables & Linear Regression

Front

What is a two-way table?

Back

A two-way table is a statistical table that displays the frequency distribution of variables. It shows the relationship between two categorical variables.

Front

Define correlation coefficient.

Back

The correlation coefficient is 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 -0.9 indicate?

Back

A correlation coefficient of -0.9 indicates a strong negative correlation, meaning that as one variable increases, the other variable tends to decrease.

Front

What is linear regression?

Back

Linear regression is a statistical method used to model the relationship between a dependent variable and one or more independent variables by fitting a linear equation to observed data.

Front

What is the line of best fit?

Back

The line of best fit is a straight line that best represents the data on a scatter plot, minimizing the distance between the line and all data points.

Front

How do you interpret a strong negative correlation in a scatterplot?

Back

A strong negative correlation in a scatterplot indicates that as one variable increases, the other variable tends to decrease significantly.

Front

What percentage of a group is calculated using a two-way table?

Back

The percentage of a group can be calculated by dividing the frequency of the subgroup by the total frequency and multiplying by 100.

Front

What does a correlation coefficient of 1 signify?

Back

A correlation coefficient of 1 signifies a perfect positive correlation, meaning that both variables move in the same direction.

Front

How can you determine the percentage of a subgroup in a two-way table?

Back

To determine the percentage of a subgroup, divide the count of the subgroup by the total count in the table and multiply by 100.

Front

What is the formula for the line of best fit in linear regression?

Back

The formula for the line of best fit is typically expressed as y = mx + b, where m is the slope and b is the y-intercept.