Stats Chapter 2

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SusanneS28
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127791
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Stats Chapter 2
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2012-01-15 10:33:51
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Stats Chapter 2
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  1. Frequency Distribution
    • A table
    • that shows classes or intervals of data with a count of the number of
    • entries in each class.
    • The frequency, f, of a
    • class is the number of data entries in the class.
  2. Midpoint of a class
    Lower class limit + Upper class limit divided by 2
  3. Class boundaries
    • The
    • numbers that separate classes without forming gaps between them..
    • The
    • distance from the upper limit of the first class to the lower limit of the
    • second class is 19 – 18 = 1.
    • Half
    • this distance is 0.5.
  4. Relative Frequency Histogram
    • Has the
    • same shape and the same horizontal scale as the corresponding frequency
    • histogram.
    • The
    • vertical scale measures the relative frequencies, not
    • frequencies.
  5. Measure of central tendency
    • A value
    • that represents a typical, or central, entry of a data set.
    • Most
    • common measures of central tendency:
    • §Mean
    • §Median
    • §Mode
  6. Mean (average)
    • The sum of all the data
    • entries divided by the number of entries.
    • Sigma
    • notation: Σx = add all of the data
    • entries (x) in the data set.
    • Population mean: u=Ex/N
    • Sample mean:x=Ex/n
  7. Median
    • The value that lies in the
    • middle of the data when the data set is ordered.
    • Measures the center of an
    • ordered data set by dividing it into two equal parts.
    • If the data set has an
    • §odd number
    • of entries: median is the middle data entry.
    • §even
    • number of entries: median is the mean of the two middle data entries.
  8. Mode
    • The data entry that occurs
    • with the greatest frequency.
    • If no entry is repeated the
    • data set has no mode.
    • If two entries occur with
    • the same greatest frequency, each entry is a mode (bimodal).
  9. Range
    • The
    • difference between the maximum and minimum data entries in the set.
    • The data
    • must be quantitative.
    • Range =
    • (Max. data entry) – (Min. data entry)
  10. Deviation
    • The
    • difference between the data entry, x, and the mean of the data set.
    • Population
    • data set:
    • §Deviation
    • of x = xμ
    • Sample
    • data set:
    • §Deviation
    • of x = xx
  11. Fractiles
    • are numbers that partition (divide) an
    • ordered data set into equal parts.
  12. Quartiles
    • approximately divide an ordered data
    • set into four equal parts.
  13. Interquartile Range (IQR)
    • The
    • difference between the third and first quartiles.
    • IQR = Q3Q1
  14. Standard Score (z-score)
    • Represents
    • the number of standard deviations a given value x falls from the mean μ.
  15. arithmetic mean
    • The arithmetic mean of a
    • variable is computed by determining the sum of all the values of the variable
    • in the data set divided by the number of observations.
  16. population arithmetic mean
    • The population arithmetic mean is
    • computed using all the individuals in a
    • population.
    • The population mean is a parameter.
    • The population arithmetic mean is denoted by u .
  17. sample arithmetic mean
    • The sample arithmetic mean is
    • computed using sample data.
    • The sample mean is a statistic.
    • The sample arithmetic mean is denoted by x.
  18. the
    population mean, µ, is
    u = x1 + x2 + xn/N
  19. the sample mean, x , is
    x = x1 + x2 + xn/n
  20. resistant
    • A numerical summary of data is said to be resistant if extreme values (very large or small) relative to the
    • data do not affect its value substantially.
  21. sample variance
    • The sample variance is
    • computed by determining the sum of squared deviations about the sample mean and
    • then dividing this result by n – 1.

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