5 Histograms

In this chapter, we’ll look at how we can use z-scores for each data point to abstract the notion of how spread out the data is. We can also use these to test whether the data appears to come from what is called a ”normal distribution” which most randomly generated data should follow. This In part B we will then use z-scores to help us build a good graphical representation of the data with a histogram. This type of graph gives a more detailed picture of the observations of a single variable and helps to classify data into one of several types. This classification then makes it easier to draw conclusions from the data.

As a result of this chapter, students will learn

As a result of this chapter, students will be able to

√: How z-scores determine a relative ranking of observations
√: How z-scores allow for comparison of data that is in different units and of different sizes
√: What normally distributed data is and what the ”rules of thumb” are for checking it
√: The difference between absolute and relative cell references
√: The characteristics of each of the classic histograms: uniform, symmetric, bimodal, positively and negatively skewed
√: How to check the rules of thumb using a histogram of z-scores
√: The characteristics of good and bad histograms

√: Compute z-scores by hand or with software
√: Explain why the standard deviation formula is set up the way it is
√: Check the rules of thumb for the spread of data
√: Read a histogram
√: Interpret the information in a histogram
√: Make a histogram of data either by hand or with software
√: Improve on a badly made histogram in order to tease more information from it

Chapter 5Histograms1

Chapter 5
Histograms¹