Explore various types of graphs such as histograms, pie charts, stemplots, and boxplots for effective data visualization and analysis in this informative review session. Learn how each graph serves a specific purpose and how they can be applied to different data sets.
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1 of 10 Histogram Similar to bar graph, but quantitative, and bars (usually) touch Good for larger data sets Break values into classes Break up range (max-min), use judgment on # Display count ( frequency ) in each class
2 of 10 Pie chart Categorical Warnings: Must include all categories And (next slide) Yes, 3 Male, 10 Female, 16 No, 19
4 of 10 Stemplot ( stem-and-leaf ) Quantitative 1. Separate into stems (usually all but last digit) and a leaf (usually last digit) 2. Stems in vertical column, consecutive. 3. Vertical line. Each leaf matches, consecutive.
5 of 10 P.1 Measures of Center 0 3 0 3 0 Mean vs. Median 3 1 4 4.35 hours Only when data is ~symmetric! 3 hours 1 5 1 5 1 5 1 7 1.5 7 2 8 2 8 2 10 2.5 10 2.5 12 3 20
6 of 10 n = 30n = 28 5-number summary 2 P.2 Minimum First quartile (25th percentile) Median Third quartile (75th percentile) Maximum 2 0 2 0 2 0 Interquartile range 3 0 3 0 3 0 3 0 3 0 Min 0 0 3.5 0 Q1 0 0 4 1 1.5 x IQR Rule for Outliers An observation is an outlier if it falls more than (1.5xIQR) above Q3 or below Q1. Q1 - (1.5xIQR) Q3 + (1.5xIQR) Med 2 2 5 1 Q3 5 1 3 3 8 2 Max 9 5 9 2 2
7 of 10 Standard Deviation P.2 0 2 0 Average distance from mean. Average of the squares of the deviations from the mean Only use when the mean is chosen as the measure of center Sensitive to outliers 2 0 2 0 2 0 3 0 3 0 2.25 3 0 3 or 1.54 0 3 1 3.5 1 4 1 5 2 5 2 8 2 9
9 of 10 Types of graphs Quantitative Histogram (Good for large data sets) Dotplot Stemplot Boxplot (Modified good for outliers) Categorical Bar graph Pie chart
10 of 10 SOCS SOCS S HAPE Skewed Symmetric Usually Use 1.5xIQR rule or modified boxplot O UTLIERS Usually not Mean x = sum/n C ENTER Median Interquartile range (IQR) Q3 Q1 Standard deviation Stat:Calc:1 S PREAD
