File 498 Doc 27 03dm Exploratorydataanalysis

ผู้ช่วยศาสตราจารย์จิรัฎฐา ภูบุญอบ ( jiratta . [email_address] . ac . th, 08-9275-9797 ) EXPLORATORY DATA ANALYSIS 3

1. Hypothesis Testing Versus Exploratory Data Analysis ,[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]

1. Hypothesis Testing Versus Exploratory Data Analysis (cont’d) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

2. Getting to Know the Data Set ,[object Object],[object Object],[object Object],[object Object]

2. Getting to Know the Data Set (cont’d) ,[object Object]

3. Dealing with Correlated Variables ,[object Object],[object Object],[object Object],[object Object],[object Object]

3. Dealing with Correlated Variables (cont’d) ,[object Object],[object Object],[object Object],[object Object],[object Object],Regression Analysis: Day Charge versus Day Mins The regression equation is Day Charge =0.000613 + 0.170 Day Mins Predictor Coef SE Coef T P Constant 0.0006134 0.0001711 3.59 0.000 Day Mins 0.170000 0.000001 186644.31 0.000 S = 0.002864 R-Sq = 100.0% R-Sq(adj) = 100.0%

3. Dealing with Correlated Variables (cont’d) ,[object Object],[object Object],[object Object],[object Object],[object Object]

4. Exploring Categorical Variables ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

4. Exploring Categorical Variables (cont’d) ,[object Object],[object Object],[object Object],[object Object]

4. Exploring Categorical Variables (cont’d) ,[object Object],[object Object],[object Object],[object Object],[object Object]

4. Exploring Categorical Variables (cont’d) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],137 346 True. 186 2,664 False. yes no Churn

4. Exploring Categorical Variables (cont’d) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

4. Exploring Categorical Variables (cont’d) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],80 403 True. 842 2,008 False. yes no Churn

4. Exploring Categorical Variables (cont’d) ,[object Object],[object Object],[object Object]

5. Exploring Numeric Variables ,[object Object],[object Object],[object Object],[object Object],[object Object]

5. Exploring Numeric Variables (cont’d) ,[object Object],[object Object],[object Object],[object Object],[object Object]

5. Exploring Numeric Variables (cont’d) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

5. Exploring Numeric Variables (cont’d) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

5. Exploring Numeric Variables (cont’d)

6. Exploring Multivariate Relationships ,[object Object],[object Object],[object Object],[object Object],[object Object]

6. Exploring Multivariate Relationships (cont’d) ,[object Object],[object Object],[object Object],[object Object]

7. Selecting Interesting Subsets of the Data for Further Investigation ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

8. Binning ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

8. Binning (cont’d) ,[object Object],[object Object],[object Object],[object Object],[object Object]

File 498 Doc 27 03dm Exploratorydataanalysis

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File 498 Doc 27 03dm Exploratorydataanalysis