Exploring Interquartile Range and Mean Absolute Deviation

What is the primary focus of the section on box and whisker plots?

• Understanding variation in data

• Learning about different types of graphs

• Calculating mean and median

• Solving algebraic equations

What is the first step in calculating the interquartile range?

• Find the median of the data

• Order the data from least to greatest

• Calculate the mean of the data

• Identify the maximum and minimum values

What is the purpose of ordering the data from least to greatest when calculating the interquartile range?

• To simplify the calculation of the median

• To calculate the mean more accurately

• To find the mode of the data

• To prepare data for graph plotting

What does the third quartile represent in a data set?

• The median of the upper half of the dataset

• The average value of the dataset

• The median of the lower half of the dataset

• The median of the entire dataset

Which quartile is calculated as the median of the upper half of the dataset?

• Fourth quartile

• Second quartile

• First quartile

• Third quartile

How is the interquartile range calculated?

• Add the first and third quartiles

• Multiply the first quartile by the third quartile

• Subtract the first quartile from the third quartile

• Divide the sum of the first and third quartiles by two

What statistical measure is used to understand how spread out the data points are from the mean?

• Variance

• Standard deviation

• Mean absolute deviation

• Range

What is the mean absolute deviation of the temperature data provided?

• 6 degrees Fahrenheit

• 5 degrees Fahrenheit

• 3.5 degrees Fahrenheit

• 4.5 degrees Fahrenheit

What does the mean absolute deviation tell us about a dataset?

• The difference between the highest and lowest values

• The most common value in the dataset

• The total range of the dataset

• The average distance each data point is from the mean

If the mean absolute deviation is small, what can be inferred about the dataset?

• There is no variation in the data

• Data points are closely packed

• Data points are widely spread out

• The dataset contains outliers