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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 thigs: it’s shape,

its center, and its spread

We desrie the shape of a distriutio i ters of its odels, it’s syetry, ad

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 distriutio hose histogra does’t appear to hae ay ode ad i hih

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 aay

Calculating the average/mean-

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