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Lecture 2
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A descriptive technique An organized tabulation showing exactly how many individuals are located in each category on the scale of measurement
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8, 9, 8, 7, 10, 9, 6, 4, 9, 8, 7, 8, 10, 9, 8, 6, 9, 7, 8, 8 Xf
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Called relative frequencies Proportion calculated by: Percentage calculated by:
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xf x fp%
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Used when the set of data has a very wide range of values In a grouped table, the X column lists groups of scores, called class intervals, rather than individual values. These intervals all have the same width, usually a simple number such as 2, 5, 10, and so on. Each interval begins with a value that is a multiple of the interval width.
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Table should have approx. 10 intervals Width of the intervals should be a relatively simple number (e.g., 2, 5, 10, 20) The bottom score in each interval should be a multiple of the width All intervals should be the same width, and should not overlap.
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Scores 973625214 3126746113 795816627 779301823 42781066 82
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Techniques used to specify the location of a particular score within the entire distribution of scores
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Shows the frequency, proportion or % of the distribution that occur at OR below a particular score Start at the lowest score, and add each corresponding frequency as you go to the highest score
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xfp%cfcpc% 102.110 95.2525 87.3535 73.1515 62.1010 5000 41.055 Relative FrequenciesCumulative Frequencies
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In a frequency distribution graph, the score categories (X values) are listed on the X axis and the frequencies are listed on the Y axis. When to use a histogram or a polygon:
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Abscissa Graphing Guideline: Include a descriptive title for the graph. Label each axis.
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Smooth Curve The smooth curve emphasizes the fact that the distribution is not showing the exact frequency for each category.
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Used when you have a nominal or ordinal scale
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Developed by Tukey (1977) and gives the same type of information as a histogram Each score is separated into two parts: ◦ the stem, which is the first digit ◦ the leaf, which is the second digit Advantages
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Example 82 75 88 93 53 84 87 58 72 94 69 84 61 91 64 87 84 70 76 89 75 80 73 78 60
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Normal Distribution Positively Skewed Negatively Skewed
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