BMGT 230 Chapter 3: BMGT230 – Chapter 3 Textbook Notes

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BMGT230 Textbook Notes Chapter 3 Displaying and Describing Quantitative Data
As mentioned in chapter 2, the first rule of data analysis is to make a picture
o Ex: Stock price is a quantitative variable and its units are dollars, so a bar or pie
chart o’t ork
o For quantitative variables, there are no categories
We slice up all the possible values into bins and then count the number of cases that fall
into each bin
o The bins along with the counts give the distribution of the quantitative variable
and provide the building blocks for the display of the distribution, called a
histogram
Histogram plots the bin counts as the heights of bars
o Unlike a bar chart, there are no gaps between bars to separate the categories
Gaps indicate a region where there are no values
o For categorical values, each category has its own bar
o For quantitative variables, we have to choose the width of the bins
Relative frequency histogram reports the percentage of cases in each bin
o Relative frequency histogram is faithful to the area principle by displaying the
percentage of cases in each bin instead of the count
Stem-and-leaf displays are like histograms, but they also show the
individual values
o Great way to look at a small batch of values quickly
o Stem and leaf breaks each number into two parts; the stem shown
to the left of the solid line and the leaf, to the right
Qualitative Data Condition: the data must be values of a quantitative variable whose
units are known.
When you describe a distribution, you should pay attentio to three thigs: it’s shape,
its center, and its spread
We desrie the shape of a distriutio i ters of its odels, it’s syetry, ad
whether it has any gaps or outlying values
Modes humps in a histogram
o A distribution whose histogram has one main hump is called unimodal
o Distributions whose histograms have tow humps are bimodal
o Those with three or more are called multimodal
o A distriutio hose histogra does’t appear to hae ay ode ad i hih
all the bars are approximately the same height is called uniform
A distribution is symmetric if the halves on either side of the center look like mirror
images
Tails thinner ends of a distribution; if one tail stretches out farther than the other, the
distribution is said to be skewed to the side of the longer tail
Outliers that stand off away from the body of the distribution should always be pointed
out; do’t just thro it aay
Calculating the average/mean-
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