This lesson is optional because it revisits below grade-level content. If the pre-unit diagnostic assessment indicates that your students know how to calculate the mean, median, mean absolute deviation (MAD), and interquartile range (IQR) then this lesson may be safely skipped. This lesson connects to upcoming work because students will interpret data using measures of center and measures of variability throughout the unit, so it is important that they understand what these statistics mean. When students explain the MAD using the meter stick example they are engaging in MP2 because they were reasoning abstractly and quantitatively by interpreting the MAD in context.
- Calculate mean absolute deviation, interquartile range, mean, and median.
- Let’s calculate measures of center and measures of variability and know which are most appropriate for the data.
You will need a meter stick and 14 pennies (or other small weights) for a demonstration. An optional blackline master is included as a graphic organizer for computing interquartile range. One copy of the blackline master contains 2 graphic organizers.
- I can calculate mean absolute deviation, interquartile range, mean, and median for a set of data.
A distribution whose dot plot or histogram takes the form of a bell with most of the data clustered near the center and fewer points farther from the center.
A distribution with two very common data values seen in a dot plot or histogram as distinct peaks. In the dot plot shown, the two common data values are 2 and 7,
A distribution where one side of the distribution has more values farther from the bulk of the data than the other side, so that the mean is not equal to the median. In the dot plot shown, the data values on the left, such as 1, 2, and 3, are further from the bulk of the data than the data values on the right.
A distribution with a vertical line of symmetry in the center of the graphical representation, so that the mean is equal to the median. In the dot plot shown, the distribution is symmetric about the data value 5.
A distribution which has the data values evenly distributed throughout the range of the data.
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