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Lesson 3 Exploring Data with Graphs and Numerical Summaries

Lesson 3 Exploring Data with Graphs and Numerical Summaries Learn …. The Use of Graphs to Describe Quantitative Data Numerical Measures for Central Tendency Graphs for Quantitative Data Dot Plot: shows a dot for each observation

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Lesson 3 Exploring Data with Graphs and Numerical Summaries

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  1. Lesson 3Exploring Data with Graphs and Numerical Summaries • Learn …. The Use of Graphs to Describe Quantitative Data Numerical Measures for Central Tendency

  2. Graphs for Quantitative Data • Dot Plot: shows a dot for each observation • Stem-and-Leaf Plot: portrays the individual observations • Histogram: uses bars to portray the data

  3. Example: Sodium and Sugar Amounts in Cereals

  4. Dotplot for Sodium in Cereals • Sodium Data: 0 210 260 125 220 290 210 140 220 200 125 170 250 150 170 70 230 200 290 180

  5. Stem-and-Leaf Plot for Sodium in Cereal Sodium Data: 0 210 260 125 220 290 210 140 220 200 125 170 250 150 170 70 230 200 290 180

  6. Frequency Table Sodium Data: 0 210 260 125 220 290 210 140 220 200 125 170 250 150 170 70 230 200 290 180

  7. Histogram for Sodium in Cereals

  8. Which Graph? • Dot-plot and stem-and-leaf plot: • More useful for small data sets • Data values are retained • Histogram • More useful for large data sets • Most compact display • More flexibility in defining intervals

  9. Shape of a Distribution • Overall pattern • Clusters? • Outliers? • Symmetric? • Skewed? • Unimodal? • Bimodal?

  10. Symmetric or Skewed ?

  11. Example: Hours of TV Watching

  12. Identify the minimum and maximum sugar values:

  13. Consider a data set containing IQ scores for the general public: What shape would you expect a histogram of this data set to have? • Symmetric • Skewed to the left • Skewed to the right • Bimodal

  14. Consider a data set of the scores of students on a very easy exam in which most score very well but a few score very poorly: What shape would you expect a histogram of this data set to have? • Symmetric • Skewed to the left • Skewed to the right • Bimodal

  15. Section 2.3 How Can We describe the Center of Quantitative Data?

  16. Mean • The sum of the observations divided by the number of observations

  17. Median • The midpoint of the observations when they are ordered from the smallest to the largest (or from the largest to the smallest)

  18. Find the mean and median CO2 Pollution levels in 8 largest nations measured in metric tons per person: 2.3 1.1 19.7 9.8 1.8 1.2 0.7 0.2 • Mean = 4.6 Median = 1.5 • Mean = 4.6 Median = 5.8 • Mean = 1.5 Median = 4.6

  19. Outlier • An observation that falls well above or below the overall set of data • The mean can be highly influenced by an outlier • The median is resistant: not affected by an outlier

  20. Mode • The value that occurs most frequently. • The mode is most often used with categorical data

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