Scatterplots and its Line of best fit

Front

What is a scatterplot?

Back

A scatterplot is a graphical representation of two variables, where each point represents an observation in the dataset, plotted along two axes.

Front

What does the line of best fit represent in a scatterplot?

Back

The line of best fit represents the trend in the data, showing the general direction that the data points follow.

Front

How do you determine the line of best fit for a scatterplot?

Back

The line of best fit can be determined using statistical methods such as least squares regression, which minimizes the distance between the data points and the line.

Front

What is the purpose of the line of best fit?

Back

The purpose of the line of best fit is to make predictions about one variable based on the value of another variable.

Front

What does a positive correlation in a scatterplot indicate?

Back

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

Front

What does a negative correlation in a scatterplot indicate?

Back

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

Front

What does no association in a scatterplot mean?

Back

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

Front

What is the significance of outliers in a scatterplot?

Back

Outliers are data points that fall far from the trend of the rest of the data; they can significantly affect the line of best fit and the overall analysis.

Front

How can you visually identify the line of best fit on a scatterplot?

Back

The line of best fit can be visually identified as the line that best represents the trend of the data points, minimizing the distance from all points.

Front

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

Back

The slope (m) of the line of best fit is calculated as m = (NΣ(xy) - ΣxΣy) / (NΣ(x^2) - (Σx)^2), where N is the number of data points.