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[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Mean  = 519/ 240 =  2.163  No. of Children (X) No. of families ( f ) Total no of children (fx) 0 30 0 x 30 =  0 1 52 1 x 52 =  52 2 60 2 x 60 = 120 3 65 3 x 65 = 195 4 18 4 x 18 =  72 5 10 5 x 10 =  50 6 5 6 x  5  =  30 Total = 240 = 519
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object]
5, 4, 6, 11, 5, 7, 10, 5 The mode is 5.
[object Object],[object Object],[object Object],a.   5  5  5  3  1  5  1  4  3  5 b.   1  2  2  2  3  4  5  6  6  6  7  9 c.   1  2  3  6  7  8  9  10 Examples
Merits Demerits ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],Definitions
Skewness Mode  =  Mean  =  Median SYMMETRIC Figure  2-13 (b)
Skewness Mode  =  Mean  =  Median SKEWED LEFT (negatively ) SYMMETRIC Mean  Mode  Median Figure  2-13 (b) Figure  2-13 (a)
Skewness Mode  =  Mean  =  Median SKEWED LEFT (negatively ) SYMMETRIC Mean  Mode  Median SKEWED RIGHT (positively) Mean  Mode  Median Figure  2-13 (b) Figure  2-13 (a) Figure  2-13 (c)
[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],Mean deviation (MD ) = _ Σ X - X = ------------ n   =  6 / 7  =  0.85 Observation (X) __ Mean (  X ) __ Deviation (X -  X) 10 __  X  =  Σ X  / n  =  63 / 7 =  9 1 9 0 11 2 7 -2 8 -1 9 0 9 0 ΣX=63 _ Σ (X-X) = 6, ignoring + or - signs
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
S.D ( σ  ) =  = Σ(X  –X)   2   / n-1  =(√1924/ (12-1)  _____ = √174  = 13.2 Observation (X) __ Mean ( X ) _ Deviation (X- X) __ (X-X)   2   58 __ X  =  Σ X / n =  984/12 =  82 -12 576 66 -16 256 70 -12 144 74 -8 64 80 -2 4 86 -4 16 90 8 64 100 18 324 79 -3 9 96 14 196 88 6 36 97 15 225 Σ X = 984 _ Σ (X - X) 2  =1914
Estimation of Standard Deviation Range Rule of Thumb x   -  2 s x   x   +  2 s Range    4 s or (minimum usual  value) (maximum usual  value)
Estimation of Standard Deviation Range Rule of Thumb x   -  2 s x   x   +  2 s Range    4 s or (minimum usual  value) (maximum usual  value) Range 4 s  
Estimation of Standard Deviation Range Rule of Thumb x   -  2 s x   x   +  2 s Range    4 s or (minimum usual  value) (maximum usual  value) Range 4 s   = highest value - lowest value 4
 
[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object]
x   The Empirical Rule (applies to bell-shaped distributions ) FIGURE 2-15
x  -  s x   x   +   s 68% within 1 standard deviation 34% 34% The Empirical Rule (applies to bell-shaped distributions ) FIGURE 2-15
x  -  2s x  -  s x   x   +   2s x   +   s 68% within 1 standard deviation 34% 34% 95% within  2 standard deviations The Empirical Rule (applies to bell-shaped distributions ) 13.5% 13.5% FIGURE 2-15
x  -  3s x  -  2s x  -  s x   x   +   2s x   +   3s x   +   s 68% within 1 standard deviation 34% 34% 95% within  2 standard deviations 99.7% of data are within 3 standard deviations of the mean The Empirical Rule (applies to bell-shaped distributions ) 0.1% 2.4% 2.4% 13.5% 13.5% FIGURE 2-15 0.1%

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Mean, median, and mode ug

  • 1.
  • 2.
  • 3.
  • 4.
  • 5.
  • 6. 5, 4, 6, 11, 5, 7, 10, 5 The mode is 5.
  • 7.
  • 8.
  • 9.
  • 10. Skewness Mode = Mean = Median SYMMETRIC Figure 2-13 (b)
  • 11. Skewness Mode = Mean = Median SKEWED LEFT (negatively ) SYMMETRIC Mean Mode Median Figure 2-13 (b) Figure 2-13 (a)
  • 12. Skewness Mode = Mean = Median SKEWED LEFT (negatively ) SYMMETRIC Mean Mode Median SKEWED RIGHT (positively) Mean Mode Median Figure 2-13 (b) Figure 2-13 (a) Figure 2-13 (c)
  • 13.
  • 14.
  • 15.
  • 16.
  • 17.
  • 18.
  • 19. S.D ( σ ) = = Σ(X –X) 2 / n-1 =(√1924/ (12-1) _____ = √174 = 13.2 Observation (X) __ Mean ( X ) _ Deviation (X- X) __ (X-X) 2 58 __ X = Σ X / n = 984/12 = 82 -12 576 66 -16 256 70 -12 144 74 -8 64 80 -2 4 86 -4 16 90 8 64 100 18 324 79 -3 9 96 14 196 88 6 36 97 15 225 Σ X = 984 _ Σ (X - X) 2 =1914
  • 20. Estimation of Standard Deviation Range Rule of Thumb x - 2 s x x + 2 s Range  4 s or (minimum usual value) (maximum usual value)
  • 21. Estimation of Standard Deviation Range Rule of Thumb x - 2 s x x + 2 s Range  4 s or (minimum usual value) (maximum usual value) Range 4 s 
  • 22. Estimation of Standard Deviation Range Rule of Thumb x - 2 s x x + 2 s Range  4 s or (minimum usual value) (maximum usual value) Range 4 s  = highest value - lowest value 4
  • 23.  
  • 24.
  • 25.
  • 26. x The Empirical Rule (applies to bell-shaped distributions ) FIGURE 2-15
  • 27. x - s x x + s 68% within 1 standard deviation 34% 34% The Empirical Rule (applies to bell-shaped distributions ) FIGURE 2-15
  • 28. x - 2s x - s x x + 2s x + s 68% within 1 standard deviation 34% 34% 95% within 2 standard deviations The Empirical Rule (applies to bell-shaped distributions ) 13.5% 13.5% FIGURE 2-15
  • 29. x - 3s x - 2s x - s x x + 2s x + 3s x + s 68% within 1 standard deviation 34% 34% 95% within 2 standard deviations 99.7% of data are within 3 standard deviations of the mean The Empirical Rule (applies to bell-shaped distributions ) 0.1% 2.4% 2.4% 13.5% 13.5% FIGURE 2-15 0.1%

Notas del editor

  1. page 58 of text Name the two values if the set is bimodal
  2. Data skewed to the left is said to be ‘negatively skewed’ with the mean and median to the left of the mode. Data skewed to the right is said to be ‘positively skewed’ with the mean and media to the right of the mode.
  3. Data not ‘lopsided’.
  4. Data lopsided to left (or slants down to the left - definition of skew is ‘slanting’)
  5. Data lopsided to the right (or slants down to the right)
  6. Reminder: range is the highest score minus the lowest score
  7. Reminder: range is the highest score minus the lowest score
  8. Reminder: range is the highest score minus the lowest score
  9. These ideas will be used repeatedly throughout the course.
  10. page 79 of text
  11. Some student have difficulty understand the idea of ‘within one standard deviation of the mean’. Emphasize that this means the interval from one standard deviation below the mean to one standard deviation above the mean.
  12. These percentages will be verified by the concepts learned in Chapter 5. Emphasize the Empirical Rule is appropriate for data that is in a BELL-SHAPED distribution.