Stat Vocab 3

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Stat Vocab 3
2012-09-02 22:21:38

stat vocab 3
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  1. Histogram (relative frequency histogram)
    A histogram uses adjacent bars to show the distribution of values in a quantitative variable.

    (Each bar represents the frequency [or relative frequency] of values falling in an interval of values)
  2. Steam-and-leaf Dispay
    A stem-and-leaf display shows quantitative data values in a way that sketches the dsitribution of the data. It's best described in detail by example.
  3. Dotplot
    A dotplot graphs a dot for each case against a single axis
  4. Shape
    To describe the shape of a distribution, look for

    • --single vs. multiple modes
    • --symmetry vs. skewness
  5. Center
    A value that attempts the impossible by summarizing the entire distribution with a single number, a "typical" value.
  6. Spread
    A numerical summary of how tightly the values are clustered around the "center"'
  7. Mode
    A hump or local high point in the shape of the distribution of a variable is called a "mode." The apparent location of modes can change as the scale of a histogram is changed.
  8. Unimodal
    Having one mode. This is a useful term for describing the shape of a histogram when it's generally mound-shaped. Distributions with two modes are bimodal. Those with more than two are multimodal.
  9. Uniform
    A distribution that's roughly flat is said to be uniform
  10. Symmetric
    A distribution is symmetric if the two halves on either side of the center look approxiamtely like mirror images of each other.
  11. Tails
    The tails of distribution are the parts that typically trail off on either side. Distributions can be characterized as having long tails (if they straggle off for some distance) or short tails (if they don't)
  12. Skewed
    A distribution is skewed if it's not symmetric and one tail stretches out farther than the other. Distributions are said to be skewed left when the longer tail stretches to the left, and skewed right when it goes to the right.
  13. Outliers
    Outliers are extreme values that don't appear to belong with the rest of the data. They may be unusual values that deserve further investigation, or just mistakes; there's no obvious way to tell. Don't delete outliers automatically--you have to think about them. Outliers may affect many statistical analysis, so you should always be alert for them.
  14. Timeplot
    A timeplot displays data that change over time. Often, successive values are connected with lines to show trends more clearly.