02_Chapter 02 - Click to edit Master subtitle style Ch 1 2 Examining Your Data 11 Ch 1 CONTENT Missing Data Outliers 22 Ch 1 M issing Data 33

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Unformatted text preview: Click to edit Master subtitle style Ch 1 2. Examining Your Data 11 Ch 1 CONTENT Missing Data Outliers 22 Ch 1 M issing Data 33 Missing Data Non- Ignorable Nonsample d observatio n Censor ed data Refus al No Opinion Ignorable Ch 1 M issing Data Impact Sample size reduction Low generalizability of the results 44 Ch 1 M issing Data Remedies Systematic missing Variables with 20% or move missing value Respondents with 20% or more missing responses Deletion Random missing Missing at random (MAR) Missing completely at random (MCAR) Statistical remedies only for MCAR 55 Ch 1 M issing Data Remedies Randomness Diagnosis Missing responses in “Income” ▪ Create two groups ▪ 1: Income-missing l People who did not respond to “Income” ▪ 2: Income-not-missing l People who responded to “income” Do other variables differ between the “income-missing” and “income-not- missing” groups 66 Ch 1 M issing Data Remedies Difference in “Gender” (non- metric/nominal) between “Income- missing” and “Income-not-missing” groups ▪ Chi-square Difference in “Spending” or “Attitude” (metric/scale) between “Income- missing” and “Income-not-missing” groups ▪ T-test 77 Ch 1 M issing Data Remedies Significant difference ▪ MAR ▪ Collect more data Insignificant difference ▪ MCAR ▪ Substitution 88 Ch 1 M iss Data Remedies - Sample data Missing Data Chapter 2.sav id: respondent identification number v1 : Quality (1:poor – 10: excellent) v2: Design (1:poor – 10: excellent 99 Ch 1 Data View Ch 1 Variable View Ch 1 M iss Data Remedies - v1: Quality (1:poor – 10: excellent) v2: Design (1:poor – 10: excellent) v3: Material (1:poor – 10: excellent) v4: Safety (1:poor – 10: excellent) v5: Promotion (1:poor – 10: excellent) v6: Price (1:poor – 10: excellent) v7: Shipping (1:poor – 10: excellent) v8: Customer Service (1:poor – 10: excellent) v9: Tech Support (1:poor – 10: excellent) v10: Customer Type (0: New, 1:Existing) v11: Distribution (0: Retailer, 1: Direct Sales) v12: Region (0: North, 1: South) v13: Industry (0: Non-IT, 1: IT) 12 Ch 1 Analyze -> Descriptive Statistics -> Frequencies Ch 1 Select Quality(V1) from the variable list and next click on the arrow to enter it into Var iable(s) Ch 1 Quality (V1) is now in Var iable(s). Select Design (V2) from the variable list and next click on the arrow to enter it into Var iable(s). Repeat the same procedure for V3 to V14....
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This note was uploaded on 06/18/2011 for the course MGT 600+ taught by Professor Shen during the Spring '11 term at Saint Joseph's University.

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02_Chapter 02 - Click to edit Master subtitle style Ch 1 2 Examining Your Data 11 Ch 1 CONTENT Missing Data Outliers 22 Ch 1 M issing Data 33

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