Box Plot With Outliers

• only Hayes Road is symmetric
• Hayes Road's center is at 60
• Jefferson Road's center is at 55
• only Jefferson Road is symmetric

• the speed on Hayes Road is greater than the speed on Jefferson Road
• the speed on Jefferson Road is greater than the speed on Hayes Road
• these data sets contain no outliers
• the center of the data set are the same

• neither plot has an outlier
• Hayes Road is skewed right
• Jefferson Road's spread is less than Hayes Road's spread
• Hayes Road's center is at 55

• the median wait time for both rides is 35
• the Red Racer has a lower maximum than the Wild Viper
• the Wild Viper has a larger spread than Red Racer
• the Red Racer has a larger IQR than the Wild Viper

Consider a dataset of final exam scores for a large introductory statistics course. The instructor, Maya, uses a boxplot to visualize the distribution of scores. Interpret the outliers in this boxplot and explain their significance.

• Outliers in a boxplot are always errors in the data collection process.

• Outliers in a boxplot are data points that fall below the lower whisker or above the upper whisker, typically defined as 1.5 times the interquartile range away from the first and third quartiles. They are represented as individual points outside the main box of the plot, indicating students whose scores are significantly different from the rest.

• Outliers have no impact on the interpretation of the data.

• Outliers are always indicative of a mistake in the statistical analysis.

Which of the following is true about outliers in a box plot?

• They are always above the upper quartile

• They are always below the lower quartile

• They can be either above the upper quartile or below the lower quartile

• They are always at the median

How can the presence of outliers affect the interpretation of a box plot?

• It can make the median appear higher than it actually is

• It can distort the perceived spread of the data

• It can change the position of the first and third quartiles

• It has no effect on the interpretation

How is the upper boundary for outliers calculated in a box plot?

• Upper Quartile + (1.5 * IQR)

• Upper Quartile - (1.5 * IQR)

• Lower Quartile + (1.5 * IQR)

• Lower Quartile - (1.5 * IQR)

What is the main purpose of a boxplot in statistics?

• Show the central tendency of a data set

• Compare two data sets

• Identify the correlation between variables

• Show the distribution of a data set and detect outliers.

How do you determine if a data point is an outlier in the context of a box plot?

• It is outside the range of the box

• It is more than 1.5 IQRs from the nearest quartile

• It is the highest or lowest point in the data set

• It is not included in the calculation of the median