The more we get together
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The more we get together

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The more we get together The more we get together Presentation Transcript

  • The More We Get Together The more we get together, Together, together, The more we get together, The happier well be. For your friends are my friends, And my friends are your friends. The more we get together, The happier well be!
  • GraphicalRepresentation & Shapes of Distribution
  • A graph adds life and beauty toone’s work, but more than this, it helps facilitate comparison and interpretation without going through the numerical data.
  • Kinds of Graphs Bar Chart Histogram Frequency Polygon Pie Chart Ogive
  • Bar Chart of the Grouped Frequency Distribution for the Entrance Examination Scores of 60 18 17Students 16 14 14 12 11frequency 10 8 8 6 6 4 3 2 1 0 0 18-23 24-29 30-35 36-41 42-47 48-53 54-59 60- 65 class interval A bar chart is a graph represented by either vertical or horizontal rectangles whose bases represent the class intervals and whose heights represent the frequencies.
  • The Histogram of the Grouped Frequency Distribution for the Entrance Examination Scores 18 of 60 Students 16 14Frequency 12 10 8 6 4 2 0 20.5 26.5 32.5 38.5 44.5 50.5 56.5 class mark A histogram is a graph represented by vertical or horizontal rectangles whose bases are the class marks and whose heights are the frequencies.
  • The Frequency Polygon of the Grouped Frequency Distribution for the Entrance Examination Scores of 60 Students 18 16 14Frequency 12 10 8 6 4 2 0 14.5 20.5 26.5 32.5 38.5 44.5 50.5 56.5 62.5 class mark A frequency polygon is a line graph whose bases are the class marks and whose heights are the frequencies.
  • The Pie Chart of the Grouped FrequencyDistribution for the Entrance Examination Scores of 60 Students 5.00% 1.67% 10.00% 13.33% 18.33% 23.33% 28.33% A pie chart is a circle graph showing the proportion of each class through either the relative or percentage frequency.
  • A pie chart is drawn by dividing the circle according tothe number of classes. The size of each piece dependson the relative or percentage frequency distribution. How to compute for the Relative Frequency?
  • The relative frequency of each class is obtained bydividing the class frequency by the total frequency.Relative Frequency Distribution for the Entrance Examination Scores of 60 Students Class Midpoint Frequency Relative Interval (X) (f) Frequency (ci) (rf) 18 - 23 20.5 6 0.1000 24 - 29 26.5 11 0.1833 30 - 35 32.5 17 0.2833 36 - 41 38.5 14 0.2333 42 - 47 44.5 8 0.1333 48 - 53 50.5 3 0.0500 54 - 59 56.5 1 0.0167 N = 60
  • The Less than and Greater than Ogives for the Entrance Examination Scores of 60 Students 70C F 60u r 50 Less than ogivem eu q 40l u 30 Greater than ogivea e 20t ni c 10v y 0e 17.5 23.5 29.5 35.5 41.5 47.5 53.5 59.5 Class Boundaries An ogive is a line graph where the bases are the class boundaries and the heights are the <cf for the less than ogive and >cf for the greater than ogive.
  • Shapes ofDistribution  Symmetrical Asymmetrical
  • SYMMETRICAL DISTRIBUTIONNormal Distribution Each half or side of the distribution is a mirror image of the other side (bell-shaped appearance) Mean ,median ,and mode coincides (mean = median = mode) Skewness is equal to zero
  • ASYMMETRICAL DISTRIBUTIONNegatively Skewed/Skewedto the Left In a negative skew the tail extends far into the negative side of the Cartesian graphmean < medianSkewness is less than 0.the mass of the distributionis concentrated on the right ofthe figure
  • ASYMMETRICAL DISTRIBUTIONPositively Skewed/Skewed tothe Right In a positive skew the tail on the right side of the distribution exdends far into the positive side of the Cartesian graph.mean > medianSkewness is greater than 0.the mass of the distribution isconcentrated on the left of thefigure
  • Skewness refers to the degree of symmetry or asymmetry of a distribution. The extent of skewness can be obtained bygetting the coefficient of skewness using the formula: SK = 3(Mean – Median) Standard deviation
  • Let us summarize the measurements from the 3 types ofdistribution: Normal Skewed to Skewed to the left/ the right/ Negatively Positively skewed skewed Mean 4.00 5.58 2.40 Median 4.00 6.00 2.00 Mode 4.00 6.00 2.00 Standard 1.53 1.07 1.07 deviation
  • Using the formula to find the coefficient of skewness, we have:For normal For skewed to the leftdistribution: distribution: For skewed to the right distribution:SK= 3(Mean – Median) SK= 3(Mean – Median) Standard deviation Standard deviation SK= 3(Mean – Median) = 3(5.6 – 6.0) Standard deviation = 3(4.0 – 4.0) 1.07 = 3(2.4 – 2.0) = - 1.12 1.07 1.53 = 1.12 =0 Notice that if •SK = 0, distribution is normal •SK < 0, distribution is skewed to the left •SK > 0, distribution is skewed to the right
  • Exercise Find the coefficient of skewness and indicate if thedistribution is normal, skewed to the left or skewed to theright.72, 81, 67, 83, 61, 75, 78, 82, 71, 67 Solution: Find the mean : Mean = 73.7 Find the median: Median = 73.5 Find the SD: SD = 7.38 Find the SK: SK = 3(Mean – Median)/Standard deviation = 3(73.7 – 73.5)/ 7.38 = 0.08 Interpretation: Since SK is positive, then it is skewed to the right. But the value is too small, so we can say that the distribution is almost normal.
  • FIN Reporters: Ando, Lilian Dillo, Charlyn Lapos, Emilia