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EXPLORING DATA LESSON 1 – 1 Day 2 Displaying Distributions with Graphs Displaying quantitative variables

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What are the graphs that are used for organizing quantitative variables and how are they interpreted? Objectives: To organize quantitative data into dotplots, stemplots, and histograms. Essential Question:

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Warm up # 1 Page 11, problem 1.6 ACCIDENTAL DEATHS Make a pie chart for the data.

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Constructing a Dotplot Step 1: Label your axis and title your graph. Draw a horizontal line and label it with the variable. Step 2: Scale the axis based on the values of the variable. Step 3: Mark a dot above the number on the horizontal axis corresponding to each data value.

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Overall Pattern of Distribution To describe the overall pattern of a distribution: Step 1: Give the center and the spread. (Divide observations in half for now.) Step 2: See if the distribution has a simple shape that you can describe in a few words. ( State the smallest and largest data.) Outliers: An outlier in any graph is an individual observation that falls outside the overall pattern.

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Constructing a Stemplot Step 1: Separate each observation into a stem consisting of all but the rightmost digit and a leaf, the final digit. Step 2: Write the stems vertically in increasing order from top to bottom, and draw a vertical line to the right of the stem. Go through the data, writing each leaf to the right of its stem and spacing the leaves equally. Step 3: Write the stems again, and rearrange the leaves increasing order out from the stem. Step 4: Title your graph and add a key describing what stems and leaves represent.

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Splitting stems When there are quite a few leaves in a couple of stems, split each stems into two parts. The first will be from 0 to 4 and the second from 5 to 9.

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Tips for stemplots Whenever you split stems, be sure that each stem is assigned an equal number of possible leaf digits. There is no magic number of stems to use. Five stems is a good minimum. You can get more flexibility by rounding the data so that the final digit after rounding is suitable as a leaf. Do this when the data have too many digits.

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Constructing a Histogram Step 1: Divide the range of the data into classed of width. Count the number of observations in each class. (each observation should fall in exactly one class.) Step 2: Label and scale your aces and title your graph. Step 3: Draw a bar that represents the count in each class. The base of the bar should cover the class count. *Graphing note: It is common to add a “bread – in – scale “ symbol ( // ) on an axis that does not start at 0.

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