2 Descriptive Stats

2 Descriptive Stats - Descriptive statistics Examining a...

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Descriptive statistics: Examining a single variable graphically
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Different kinds of data height, weight, mass, volume, time, temperature, grade (in percent), IQ names, favorites, preferences, property e.g. color or gender Likert scales, classiFcation: small medium large, place Fnish, letter grade
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Categorizing data Quantitative: Measurement has a numerical value, usually has a unit of measurement Qualitative: Measurement has no meaningful numerical value, one of several categories or groups careful with counts
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Counts Depending on what you are interested in, counts of values can be either qualitative or quantitative if the count is the number of instances of some qualitative outcome (e.g. 4 people said blue), Qualitative if the count itself is the instance you are interested in (e.g. number correct), Quantitative
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Qualitative Nominal just names, no meaningful order blue, yellow, red, blue, red Ordinal names, but have an order small medium large agree, no preference, disagree can be numbers if the numbering is arbitrary
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Quantitative variables Continuous can the number be any real value (e.g. 1,1.2 1.22, 1.222, 3.1415926535…, 99.9999) Discrete or only natural (whole) numbers (e.g. 0 1 2 3 4.. nothing in-between) 1 2 3 4 1 2 3 4
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-1 0 1 2 Quantitative Interval scale – equal intervals between data points, but no “true” 0 statements like “twice as much” have no meaning Ratio scale – Equal intervals between data, and there is a “true” 0 statements like “twice as much” are meaningful (because there is a 0, these are ratio statements) -1 0 1 2 0 1 2 0 1 2
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Organizing variables Qualitative counts percentages bar graphs pie charts
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  • Spring '09
  • ?
  • Frequency, Frequency distribution, Histogram, Marshall Muir Warren Marshall Revelle Muir Warren Warren Warren, Warren Warren Warren, Revelle Warren Sixth Muir Revelle Warren Marshall Sixth Marshall

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2 Descriptive Stats - Descriptive statistics Examining a...

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