IMC Exam 2 1-4

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  1. examples of non-random sampling
    • quota sampling
    • panelling
    • postal and telephone surveys
  2. continuous data
    data that can take any value whatsoever
  3. discrete data
    data that can only take on specific values, such as money, which changes value in whole units
  4. categorical data
    data classified into a number of distinct categories
  5. ordinal data
    data that has been classified into a number of distinct ranked categories
  6. frequency distribution & relative f d
    • group the data into bands of specific values and display the frequency of occurrence of each band
    • -relative show proportions or percentages rather than frequencies
  7. cumulative f d & relative cum f d
    • can be used to show the number of items with a value less than or equal to a given figure.
    • relative show the proportion or % with a value less than or equal to a given figure
  8. lorenz curve
    visual comparison of the 2 cumulative frequency distributions
  9. histogram
    displays the number or % of items falling within a given band through the AREA of a bar
    • arithmetic mean
    • -not necessarily an observed value
    • -greatly affected by extremes
    • Population
    • -for raw data fi = 1 for each item
    • -for grouped data, use the midpoints
    • -for sample standard deviation, devide by (n-1) rather than n
    • Geometric mean
    • -useful for COMPOUNDING relationships
    • -UNDERSTATES the mean compared to the arithmetic mean
  10. value =
    value =
    value =
    formulas for median, range and intertquartile range
  11. = median

    -UNAFFECTED by extremes
  12. range =
    highest - lowest

    -considers ONLY EXTREMES
  13. interquartile range =

    -UNAFFECTED by extremes
  14. mode
    • most frequently occurring item
    • -must be observed value
    • -UNAFFECTED by extremes
  15. perfect symmetrical population
    mean = median = mode
  16. positively skewed distribution
    • mode<median<mean
  17. negatively skewed distribution
    • mean<median<mode
  18. regression is used to
    establish if a relationship exists between two factors, a regression calculation provides a l ine of best fit
  19. y = a + bx
    • linear regression
    • a = the intercept i.e. the height at which the line cuts the y-axis
    • b = slope
  20. interpolation
    where we use the regression line to estimate future results from data within an already observed range
  21. extrapolation
    where we try to estimate results from beyond our existing range of experiences and data
  22. APR
    annual percentage rate
  23. (1+APR) = (1 + r/n)^n
    • interest rate
    • r = annual flat rate
    • n = number of compounding periods pa
  24. R = e^rt -1
    continously compounded interest rate
  25. (1+r)^n
    basic discounted cash flow compound factor with n years to run
  26. Dn = Do (1 + r)^n
    depreciation where r is negative
  27. 1/(1+r)^n
    basic discount factor
  28. 1/r (1-1/(1+r)^n)
    discount annuity
  29. 1/r
    discount in perpetuity
  30. 1/e^rt
    continous compounded basic discount factor
  31. PV of borrowing/ ADF
    regular repayment of mortgage
  32. IRR
    • the rate of interest that discounts the investment flows to a net present value of zero
    • NPV is a better decision tool than IRR due to IRR limitations
    • -assuming reinvestments can be made at the IRR
    • -multiple yields (where cash flows reverse twice)

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IMC Exam 2 1-4
2012-03-09 21:49:12

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