Line of Best Fit

Front

What is a line of best fit?

Back

A line of best fit is a straight line that best represents the data on a scatter plot, showing the general direction of the data points.

Front

How do you determine the correlation between two variables?

Back

Correlation can be determined by analyzing the direction and strength of the relationship between two variables, often represented visually through a scatter plot.

Front

What does a positive correlation indicate?

Back

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

Front

What does a negative correlation indicate?

Back

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

Front

What does no correlation mean?

Back

No correlation means there is no discernible relationship between the two variables; changes in one do not predict changes in the other.

Front

How can you visually identify the correlation in a scatter plot?

Back

You can visually identify correlation in a scatter plot by observing the slope of the points: upward slope indicates positive correlation, downward slope indicates negative correlation, and a random scatter indicates no correlation.

Front

What is the purpose of a line of best fit in data analysis?

Back

The purpose of a line of best fit is to summarize the relationship between variables, making it easier to predict values and understand trends.

Front

What factors can affect the accuracy of a line of best fit?

Back

Factors that can affect the accuracy include outliers, the distribution of data points, and the choice of linear vs. non-linear models.

Front

What is the formula for calculating the slope of a line of best fit?

Back

The slope (m) of a line of best fit can be calculated using the formula m = (NΣxy - ΣxΣy) / (NΣx² - (Σx)²), where N is the number of data points.

Front

What is the significance of the y-intercept in a line of best fit?

Back

The y-intercept is the value of y when x is zero; it provides a starting point for the line and can indicate the baseline value of the dependent variable.