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Data mining assignment answers

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1. What is the missing data pattern of X (1 point)? The missing data pattern for the stated dataset is Arbitrary Data Pattern. 2. Discard the incomplete instances from X and then compute the mean, median, mode and standard deviation of each attribute (4 points). Mean: X X , N Variance:  X  X   2 S 2 N 1 , Standard Deviation: Square Root of Variance Median: x p 1 ifN  2 p  1   X  1  2 x p  x p 1  ifN  2 p M = mode(X) is the most frequently occurring value in X. Based on the Matlab, if several values are occurring few times, the smallest value is considered as Mode. If the missing values are eliminated by removing the instances including missing values, there would be a new dataset table as follows: X1 X2 X3 102 70 28 92 62 30 128 64 90 139 62 98 110 46 80 116 54 102 142 60 118 126 58 112 The results of the new dataset are shown as follows: For the first attribute X1: Mean: 119.375 Median: 121 Mode: N/A Standard deviation: 17.59 For the second attribute X2: Mean: 59.5 Median: 61 Mode: 62 Standard deviation: 7.15 For the third attribute X3: Mean: 82.25 Median: 94 Mode: N/A Standard deviation: 34.92 3. Replace all the missing values of X with the mean value of each attribute, and then compute the mean, median, mode and standard deviation of each attribute. X1 X2 X3 102 70 28 98 60 76 119.9 64 26 92 62 30 140 60.54 76 128 64 90 139 62 98 110 46 80 1 ...
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