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Eli Katsiri

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3.044 rounded to hundredths is 3.04 (because the next digit, 4, is less than 5) ... For negative numbers the absolute value is rounded. Examples: ... – PowerPoint PPT presentation

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Title: Eli Katsiri


1
Lecture 3
  • Eli Katsiri
  • School of Computer Science

2
Excel Practice test
  • February 8 (week 5) 7.30pm to 9pm
  • February 15 (week 6) exam
  • You will not be examined on the meaning of
    statistics. You do not need to interpret and
    discuss the results. You need to be able to
    produce the results using excel.
  • Simple data fomatting and data manipulation
    exercises using basic mathematical,logical and
    statistical functions , autofilling, histograms,
    descriptive statistics and pivot tables.

3
Rounding (1)
71, 72, 73 and 74 are closer to 70 than 80
75, 76, 77, 78 and 79 are closer to 80 than 70
4
How do we decide?
  • Decide which is the last digit to keep.
  • Increase it by 1 if the next digit is 5 or more
    (this is called rounding up)
  • Leave it the same if the next digit is 4 or less
    (this is called rounding down)
  • Examples
  • 3.044 rounded to hundredths is 3.04 (because the
    next digit, 4, is less than 5).
  • 3.045 rounded to hundredths is 3.05 (because the
    next digit, 5, is 5 or more).
  • 3.0447 rounded to hundredths is 3.04 (because the
    next digit, 4, is less than 5).

5
Negative numbers
  • For negative numbers the absolute value is
    rounded.
  • Examples
  • -2.1349 rounded to hundredths is -2.13
  • -2.1350 rounded to hundredths is -2.14

6
Rounding before the decimal point
  • Is 123.5 closer to 120 or 130?
  • Is 4278.3 closer to 4200 or 4300?

7
Rounding before the decimal point
  • Decide which is the digit that we want to round.
  • If this digit is bigger or equal to 5, then add 1
    to the digit on the left and make the current
    digit 0. Make all the digits to the right before
    the decimal point 0.
  • If this digit is smaller than 5, subtract 1 from
    digit on the left and make this digit 0. Make all
    the digits to the right before the decimal point
    0.

8
Round MathTrig (3)
  • Round(value,x)
  • xRound(-1.582, 1)  returns -1.6y
    Round(3.1415, 9)  no changez round(123.5,
    -1)  returns 120
  • round(4278.5,-2) gives 4300.

9
Trunc
  • 5.6341432543653654
  • 32.438191288
  • 6.3444444444444
  • To truncate these numbers to integers we
    consider only the left of the decimal point.
  • 5
  • 32
  • 6

10
examples
  • Trunc(2.1)8.4 returns 16.8
  • Trunc(2.1)2
  • 28.416.8
  • Trunc(2.18.4) returns 17
  • 2.18.417.64
  • Trunc(17.64)17

11
Trunc
  • truncation is the term for limiting the number of
    digits right of the decimal point, by discarding
    the least significant ones.

12
Mean
  • The mean of 2,8 is 5
  • The mean of 2,8,11 is 7
  • The mean on 40,60,35,20,55,30,57,45 is

13
Round(mean)
  • The rounded mean value of 40.60,35,20,55,30,57,45
    is 42

14
median
  • 5 14 30 1 2 29 12 31 3 12 13
  • 1 2 3 5 12 12 13 14 29 30 31
  • M12
  • 5 14 30 1 2 29 12 31 3 13
  • 1 2 3 5 12 13 14 29 30 31
  • M(1213)/212.5
  • 50th percentile of the data
  • The lowest number that is greater than 50 of the
    numbers in a list.

15
Mode
  • The most frequently occurring number value in the
    sample
  • If no data value occurs more than once, then the
    mode function returns NA
  • 5 14 30 1 2 29 12 31 3 12 13
  • Mode 12

16
Variance - Standard deviation
  • 1,3,5

17
Percentile - percentrank
  • The lowest number that is bigger than 90 of the
    data.
  • PERCENTILE(data,k), k0.9
  • PERCENTRANK( data, value)
  • Returns the ranking of the observation relative
    to all values in the data set.
  • E.g. p0.038 means that 3.8 of the data sample
    had lower values than our element.

18
Range
  • The largest number in the data-set minus the
    smallest number

19
Comparing data sets in terms of their statistics
  • Compare mean or median. The higher the median the
    better (higher) the data (e.g. higher the profit)
  • Compare standard deviation . The higher sd the
    more variable the data.
  • Compare histograms in terms of symmetricity and
    skewness. Do not explain what this means.

20
Logical
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