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Introduction to,[object Object],XLMiner™: ,[object Object],ASSOCIATION AND CHARTS,[object Object],XLMiner and Microsoft Office are registered trademarks of the respective owners.,[object Object]
ASSOCIATION,[object Object],Association rules are used to find out the interesting and useful relationships between data that occur frequently enough to be called a pattern (or a trend) and hence, can be formulated into a rule. Each of these rules has an if-then structure with an antecedent and a consequent and has three properties associated with it – support, confidence and lift. ,[object Object],Support is the number of records that contain both the antecedent and consequent i.e. the number of records for which the rule holds true.,[object Object],Confidence is the ratio of the support to the number of the records where the antecedent occurs (i.e. a ratio of the number of records where the rule holds true to the total number of records where antecedent occurs). ,[object Object],The third parameter is the lift.,[object Object],Lift = confidence/ (ratio of the number of records containing the consequent to the total number of records),[object Object],http://dataminingtools.net,[object Object]
ASSOCIATION,[object Object],If the data in our table is in form of 0 and 1 the wizard by default selects the “data in binary matrix format". We may choose to override this.,[object Object],http://dataminingtools.net,[object Object]
ASSOCIATION,[object Object],The conf,% of 52.89% represents that of all the persons who bought a “refbook” 52.89%  bought Childbk and cookbks together.,[object Object],Support (a)shows number of transactions containing refbks and childbks, while Support(c ) shows number of transactions  containing refbks.,[object Object],http://dataminingtools.net,[object Object]
CHARTS,[object Object],Charts allows us to view the data in a visual fashion so as to interpret it easily.,[object Object],Many sheets are created during drawing models but are kept hidden. To delete them select the “Delete hidden sheets “.,[object Object], XLMiner provides us with three different methods to view data:,[object Object],Box plot,[object Object],Histogram,[object Object],Matrix plot,[object Object],http://dataminingtools.net,[object Object]
CHARTS – BOX PLOT,[object Object],A box plot is an efficient method of displaying a five member data summary. ,[object Object],The five members are:,[object Object],[object Object]
Upper quartile
Lower quartile
Minimum data value
Maximum data valueAlso, the box plot is not affected by outliers ,[object Object], - i.e. inconsistent or aberrant data. ,[object Object],It is also used to compare values.,[object Object],	DATA SET,[object Object],http://dataminingtools.net,[object Object]
CHARTS – BOX PLOT,[object Object],Since the X-Var in the data set holds  2 values(3 and 4) 4 boxes one for each value of Y1 and Y2 are drawn.,[object Object], The notch-height represents the confidence interval around the mean. When we de-check "Notched" we do not expect the confidence interval to be displayed,[object Object],http://dataminingtools.net,[object Object]
CHARTS – HISTOGRAM,[object Object],Histogram:A histogram is a bar graph. It has frequency of occurrence on the Y axis and the variable to be examined on the X axis.,[object Object],Histograms are popular among statisticians.  Though they do not show the exact values of the data points they give a very good idea about the spread of the data and shape. ,[object Object],http://dataminingtools.net,[object Object]
CHARTS – HISTOGRAM,[object Object],This histogram shows the minimum and maximum values . The tools decides the number of intervals .Here there are 11 intervals. Each bar represents the frequency of that value in the data set.,[object Object],http://dataminingtools.net,[object Object]

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