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Chapter 4 Displaying Quantitative Data Describing One Quantitative Variable Distribution of variable –Summary of different values observed for the variable.

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Presentation on theme: "Chapter 4 Displaying Quantitative Data Describing One Quantitative Variable Distribution of variable –Summary of different values observed for the variable."— Presentation transcript:

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2 Chapter 4 Displaying Quantitative Data

3 Describing One Quantitative Variable Distribution of variable –Summary of different values observed for the variable Make a picture –Histogram –Stem-and-Leaf Display –Boxplot (next chapter)

4 Histogram of Percent of Population of Hispanic Origin

5 Stem-and-Leaf Display Picture of Distribution. Generally used for smaller data sets. Group data like histograms. Still have original values (or close to it).

6 Stem-and-Leaf Display Two columns –L–Left column: Stem –R–Right column: Leaf Leaf –C–Contains the last digit of the values. –A–Arranged in increasing order away from stem. Stem –C–Contains the rest of the values. –U–Usually arranged in increasing order from top to bottom. –J–JMP does opposite, increasing order from bottom to top!

7 Stem and Leaf Plot of Percent of Population of Hispanic Origin

8 Comparing Two Related Variables Histograms Make sure bins scaling for each histogram is the same.

9 Histograms of Female and Male Heights

10 Looking at Distributions Shape –How many humps (called modes)? None = uniform One = unimodal Two = bimodal Three or more = multimodal

11 Looking at Distributions Shape –Is it symmetric? Symmetric = roughly equal on both sides Skewed = more values on one side –Skewed Right = Tail stretches to large values –Skewed Left = Tail stretches to small values ****Skewed not screwed

12 Looking at Distributions Shape –Are there any outliers? Interesting observations in data Can impact statistical methods

13 Looking at Distributions Center –A single number to describe the data. –Calculate different numbers for center. Right now, just EYE BALL IT

14 Looking at Distributions Spread –Variation in the values Smallest observation Largest observation Take into account any outliers.


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