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# Exploring data histograms

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### Exploring data histograms

1. 1. Exploring Data Describing Distributions Graphically
2. 2. Histograms Histograms are similar to stemplots They break data into intervals so that you can determine the center, shape and spread of the distribution Unlike stemplots, each individual data point is not included in the histogram only represented in its interval
3. 3. Constructing a Histogram Step 1 – Divide the data into bins (intervals) of equal width. Be sure the data will fit into these as nicely as possible Step 2 – Create a frequency table, listing each interval and the count of the number of data in each interval Step 3 – Title and scale your graph and label your axes appropriately (Bins on x-axis, frequencies on y-axis) Step 4 – Graph your histogram. Be sure you DO NOT leave spaces between the bars unless there is an empty bin
4. 4. Patterns in Histograms • Center – • Is it skewed? If there is a tail on either side that is longer than the other the side the tail is on is considered to be skewed (think skewer) • Right skew has a few large values, but most values are small • Left skew has a few small values, but most values are large
5. 5. More Patterns • Shape Does it have one peak (unimodal)? Does it have two peaks (bimodal)? Is it symmetric? Is it roughly symmetric?
6. 6. Deviations • Spread Are there any outliers (numbers by themselves)? Are there any deviations from symmetry? What is the range of values that are being displayed?