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- 1. DATA ANALYSIS Dr. Jayesh Patidar www.drjayeshpatidar.blogspot.com
- 2. Introduction to Data Analysis Why do we analyze data? Make sense of data we have collected Basic steps in preliminary data analysis Editing Coding Tabulating 2www.drjayeshpatidar.blogspot.com
- 3. Introduction to Data Analysis Editing of data Impose minimal quality standards on the raw data Field Edit -- preliminary edit, used to detect glaring omissions and inaccuracies (often involves respondent follow up) Completeness Legibility Comprehensibility Consistency Uniformity 3www.drjayeshpatidar.blogspot.com
- 4. Introduction to Data Analysis Central office edit More complete and exacting edit Best performed by a number of editors, each looking at one part of the data Decision on how to handle item non-response and other omissions need to be made List-wise deletion (drop for all analyses) vs. case-wise deletion (drop only for present analysis) 4www.drjayeshpatidar.blogspot.com
- 5. Introduction to Data Analysis Coding -- transforming raw data into symbols (usually numbers) for tabulating, counting, and analyzing Must determine categories Completely exhaustive Mutually exclusive Assign numbers to categories Make sure to code an ID number for each completed instrument 5www.drjayeshpatidar.blogspot.com
- 6. Introduction to Data Analysis Tabulation -- counting the number of cases that fall into each category Initial tabulations should be preformed for each item One-way tabulations Determines degree of item non-response Locates errors Locates outliers Determines the data distribution 6www.drjayeshpatidar.blogspot.com
- 7. Preliminary Data Analysis Tabulation Simple Counts For example 74 families in the study own 1 car 2 families own 3 Missing data (9) 1 Family did not report Not useful for further analysis Number of Cars Number of Families 1 75 2 23 3 2 9 1 Total 101 7www.drjayeshpatidar.blogspot.com
- 8. Preliminary Data Analysis Tabulation Compute Percentages Eliminate non-responses Note – Report without missing data Number of Cars Number of Families 1 75% 2 23% 3 2% Total 100 8www.drjayeshpatidar.blogspot.com
- 9. Preliminary Data Analysis Cross Tabulation Simultaneous count of two or more items Note marginal totals are equal to frequency totals Allows researcher to determine if a relationship exists between two variables Used a final analysis step in majority of real-world applications Investigates the relationship between two ordinal-scaled variables Number of Cars Lower Income Higher Income Total 1 48 27 75 2 or More 6 19 25 Total 54 46 100 9www.drjayeshpatidar.blogspot.com
- 10. Preliminary Data Analysis Cross Tabulation To analyze the data Calculate percentages in the direction of the “causal variable” Does number of cars “cause” income level? Num ber of Cars Lower Income Higher Income Total 1 64% 36% 100% 2 or More 24% 76% 100% Total 54% 46% 100% 10www.drjayeshpatidar.blogspot.com
- 11. Preliminary Data Analysis Cross Tabulation To analyze the data Does income level “cause” number of cars? Seem like this is the case. In the direction of income – thus, income marginal totals should be 100% Num ber of Cars Lower Income Higher Income Total 1 89% 59% 75% 2 or More 11% 41% 25% Total 100% 100% 100% 11www.drjayeshpatidar.blogspot.com
- 12. Preliminary Data Analysis Cross Tabulation allows the development of hypotheses Develop by comparing percentages across Lower income more likely to have one car (89%) than the higher income group (59%) Higher income more likely to have multiple cars (41%) than the lower income group (11%) Are results statistically significant? To test must employ chi-square analysis 12www.drjayeshpatidar.blogspot.com
- 13. Types of Data ContinuousDiscrete Nominal The Assignment of Numbers for Classification Purposes; Categorical Data E.g. Sex, Blood Gr Ordinal Quantitative Values Providing a Classification According to Order or Magnitude Eg: VAS; SE Status Interval ClassificationAccording to a Continuum With Interval Equality & Subdivision Sensibility Eg: Temp. Ratio Interval Data With An Absolute Value of 0 Eg: Height; weight Measurement Scales & Types of Data 13www.drjayeshpatidar.blogspot.com
- 14. Type of Data data Kind of Quantitative comparison Qualitative Normal distribution Any distribution two 2-test, t-Test , Z test Wilcoxon;Mann- samples Z test (n>30) Whitney-test Comparison for proportion Chi Square of two one sign-test, one sample sign- test, groups sample Mc.Nemar-test t-Test one-sample - Wilcoxon-test Comparison independ. 2-test one-way analysis Kruskal- Wallis-test of more samples of variance than two one Cochran’s two-way analysis Friedman-test groups sample Q-test of variance Statistical Tests: Overview 14www.drjayeshpatidar.blogspot.com
- 15. 15www.drjayeshpatidar.blogspot.com
- 16. 16www.drjayeshpatidar.blogspot.com

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