Prob & Stat - Unit 2 Review

Front

What is the least-squares regression line?

Back

The least-squares regression line is a straight line that best fits the data points in a scatterplot, minimizing the sum of the squares of the vertical distances of the points from the line.

Front

What does the correlation coefficient (r) represent?

Back

The correlation coefficient (r) measures the strength and direction of a linear relationship between two quantitative variables, ranging from -1 to 1.

Front

What does a correlation coefficient of -0.7 indicate?

Back

A correlation coefficient of -0.7 indicates a strong negative linear relationship between the two variables.

Front

What are the key components to describe the relationship between two quantitative variables?

Back

The key components are shape, strength, direction, and outliers.

Front

What happens to the mean when an outlier is removed from a dataset?

Back

Removing an outlier typically decreases the mean if the outlier is significantly higher or lower than the other values.

Front

What is the formula for the least-squares regression line?

Back

The formula is y = mx + b, where m is the slope and b is the y-intercept.

Front

What does a positive slope in a regression line indicate?

Back

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

Front

What does a negative slope in a regression line indicate?

Back

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

Front

What is the purpose of a scatterplot?

Back

A scatterplot visually represents the relationship between two quantitative variables, helping to identify patterns, trends, and correlations.

Front

What is an outlier?

Back

An outlier is a data point that differs significantly from other observations in a dataset, potentially skewing results.