BSNS102 1

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BSNS102 1
2011-06-10 02:31:17

Statistics, Descriptive Statistics, Numerical Measures, Shape
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  1. Types of data :
    • Quantitative
    • Qualitative
  2. Quantitative data is:
    Numerical eg. age:measured in years
  3. Qualitative data is:
    Grouped/ Categorical eg. Preferred accomodation type (Budget, Tourist, Superior)
  4. Categorical data (Qualitative) is:
    • Nominal (name or number given to a category as a label)
    • Ordinal (name or number implies ranking)
  5. Numerical data (Quantitative) is:
    • Discrete (whole or counting numbers)
    • Continuous (infinite number of values eg. Age, Income)
  6. A population is the :
    Whole collection of things under consideration
  7. A sample is a:
    Portion of the poplulation selected for analysis
  8. A parameter is a:
    Summary measure that describes the characteristic of the population
  9. A statisitic is a:
    Summary measure computed that describes a characteristic of a sample.
  10. Sources of data:
    • Primary data
    • Secondary data
    • Census
    • Experimental data
    • Surveys
  11. Non sampling errors:
    • Coverage error
    • Non response error
    • Measurement error
  12. Sampling error:
    Chance differs from sample to sample
  13. Measures of central tendancy:
    • Mean (Average)
    • Median (Middle value)
    • Mode
    • Trimmed Mean (cuts out extreme 5%)
  14. Measures of spread:
    • Range (Max - Min)
    • Interquartile range (middle 50%)
    • Varience (std dev around the mean)
    • Std Deviation (square root of the varience)
  15. Measures of shape: Skewness
    • Symmetric distribution (median = mean)
    • Right skewed (Tail to the right)
    • Left skewed (Tail to the left)
  16. Measures of shape: Kurtosis
    • Positive Kurtosis: Data clusters more and have longer tails
    • Negative Kurtosis: Data is less clustered and has shorter/ fatter tails
  17. Box and whisker plots:
    • Box (shows interquartile range)
    • Line (median)
    • Whiskers (highest and lowest value)
    • Outliers
    • Extreme outliers