How do outliers affect a box and whisker plot?

Outliers can affect a box and whisker plot by influencing the placement of the whiskers and the overall shape of the plot. An outlier is a data point that is significantly different from the other values in the dataset. When an outlier is present, the whiskers of the box and whisker plot may extend further or shorter than they would without the outlier. This is because the whiskers typically extend to the minimum and maximum values within a certain range, but outliers can push these boundaries. Additionally, the presence of outliers can skew the distribution of the data, causing the box to be elongated or compressed depending on the position of the outlier.

Outliers are important because they are numbers that are "outside" of the Box Plot's upper and lower fence, though they don't affect or change any other numbers in the Box Plot your instructor will still want you to find them.

If you want to find your fences you will first take your IQR and multiply it by 1.5. I call this your "magic number".

Lower fence: Take your Q1 and subtract it from your magic number, that number your get is your lower fence.

Upper fence: Take your Q3 and add it to your magic number, that number you get is your upper fence.

Remember, any numbers that are "outside" the lower or upper fences is considered an outlier.