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1.2 - Displaying quantitative data with graphs (Histograms)

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Histograms The most common graph of quantitative data. Classes: the intervals along the bottom axis. These need to be of equal width Frequency: the count of individuals of a class occurring Relative frequency: the percent of the individuals in a class (this is more useful, especially when you are comparing two sets of data with an unequal total of individuals)

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Construct 2 histograms. One displaying the frequency and one displaying the relative frequency. The following table presents the average points scored per game (PTSG) for the 30 NBA teams in the 2009-2010 regular season. 101.799.295.397.5102.1102 106.594108.8102.4100.895.7 101.7102.596.597.798.292.4 100.2102.1101.5102.897.7110.2 98.1100101.4104.1104.296.2

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Steps for constructing a histogram 1st - divide the range of data into class of equal width. 2nd - find the count and percent of individuals in each class. 3rd - label and scale your axes 4th - draw your histogram

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1st step What is the range of our data? What would be a good class size to choose? What are the classes?

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2nd Step Fill in a frequency table and a relative frequency table. Frequency Table ClassCount Relative Frequency Table ClassPercent

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3rd step PTSG Frequency PTSG Relative Frequency

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4th step PTSG Frequency PTSG Relative Frequency

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Describe the data of the average points per game in the 2009-2010 NBA season. Don’t forget your “SOCS!” The data appears to be _______ with a peak of _____. The _____ appear to be any outliers. The center of the data occurs around ______ The histogram shows that the percent of points per games ranged from __________

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How does class size effect the shape of the histogram? www.whfreeman.com/tps4e

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Last Pieces of advice about histograms 1. Don’t confuse histograms and bar graphs Histograms are for quantitative data Bar graphs are for categorical data 4. Just because a graph looks nice, doesn’t mean it’s necessarily a meaningful display of data. (Excel is a terrible tool to use for statistical graphs) 3. Use percents instead of counts when comparing distributions with different numbers of observations. 2. Don’t use the counts or percents as the data. Use the data to find the counts and percents for your graph.

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