Calculating and Comparing Data Spread Using Interquartile Range

The video tutorial explains how to calculate and compare the spread of data sets using the interquartile range (IQR). It highlights the limitations of using range alone due to potential outliers and introduces IQR as a more reliable measure of data spread. The tutorial provides step-by-step instructions for calculating IQR and compares two classes' test scores to demonstrate the concept. The lesson concludes by emphasizing the importance of understanding data spread for effective teaching strategies.

What is the main limitation of using range as a measure of data spread?

• It only considers the middle data points.

• It requires a large data set.

• It can be skewed by outliers.

• It is difficult to calculate.

What does the interquartile range (IQR) measure?

• The spread of the entire data set.

• The spread of the middle 50% of the data.

• The difference between the maximum and minimum values.

• The average of all data points.

How is the interquartile range (IQR) calculated?

• By subtracting the minimum value from the maximum value.

• By finding the difference between the third and first quartiles.

• By adding the first and third quartiles.

• By averaging all data points.

In the example of Ms. Foxworth's class, what was the interquartile range?

• 88

• 65

• 12

• 5

What was the interquartile range for Ms. Ruiz's class?

• 65

• 12

• 5

• 88

Why might Ms. Ruiz consider a whole class review?

• The interquartile range was large.

• Her students' scores were very spread out.

• The range was the same as Ms. Foxworth's class.

• The scores were fairly close together.

What teaching strategy might be more effective for Ms. Foxworth's class?

• No review needed.

• Individual or small group review.

• Whole class review.

• Focus on outliers only.