1.2 - Displaying quantitative data with graphs (Histograms)

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Presentation transcript:

1.2 - Displaying quantitative data with graphs (Histograms)

Histograms The most common graph of quantitative data. (not the most convenient) 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)

Door Side The following table represents the battings averages for the 25 Cincinnati Reds who have an at bat this time in the 2013 season

Wall Side The following table represents the battings averages for the 29 Cincinnati Reds who have an at bat this time in the 2014 season

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

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

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

3rd step Batting Average Relative Frequency Batting Average Relative Frequency

Describe the data of the batting average for YOUR year only! 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 batting ranged from __________

Now let’s COMPARE the batting averages from 2013 and 2014

How does class size effect the shape of the histogram?

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.