Internet Usage Statistical Data Analysis

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Internet Usage Statistical Data Analysis

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Internet Usage Statistical Data Analysis

  1. 1. Internet UsageStatistical DataAnalysis Edgardo Donovan RES 610 – Dr. Joshua Shackman Module 5 – Session Long Project Monday, September 19, 2011
  2. 2. Overview 1. Study Background 2. Top/Lowest Uses 3. Top/Lowest Uses Chart 4. InterSurvey 5. Sampling Issues 6. Hypotheses 7. Case Processing 8. Reliability 9. Item Statistics 10. Item Statistics (cont.) 11. Summary Item Stats
  3. 3. Overview (cont.) 12. Inter-Item Correlations 13. More Quantitative Analysis 14. Item Statistics 15. Item Statistics (cont.) 16. Improving the Original 17. Improved USC Model 18. Autocorrelations 19. Hours on the Internet 20. Hours on Internet (cont.) 21. Positive Correlations 22. Positive Correlations (cont.)
  4. 4. Overview (cont.) 23. Conclusion 24. Questions?
  5. 5. 1. Study Background 2000 UCLA study surveying the digital future Limited to WebTV users Initially started at Stanford, then UCLA, then USC
  6. 6. 2. Top/Lowest Uses Top Uses:  Learning  Surfing (overlap?)  Reading about products Surprising Lowest Uses:  Schoolwordk  Banking  Job Search
  7. 7. 3. Top/Lowest Uses Chart
  8. 8. 4. InterSurvey Relied upon a form application tool named “Intersurvey” Survey had to be done online Low interest in effectively sampling the US Internet user population
  9. 9. 5. Sampling Issues WebTV Set Top Boxes  Limited to low end income demographic Poor attempt at sampling External validity problematic
  10. 10. 6. Hypotheses “Negative correlation between Internet and TV use Negative correlation between Internet Use and traditional social activity and shopping No insight on survey questions
  11. 11. 7. Case Processing Case Processing Summary N % Cases Valid 1241 100.0 Excludeda 0 .0 Total 1241 100.0 a. Listwise deletion based on all variables in the procedure.
  12. 12. 8. Reliability Reliability Statistics Cronbachs Alpha Based on Cronbachs Alpha Standardized Items N of Items .816 .809 17
  13. 13. 9. Item Statistics
  14. 14. 10. Item Statistics (cont.)
  15. 15. 11. Summary Item Stats
  16. 16. 12. Inter-Item Correlations
  17. 17. 13. More Quantitative Analysis
  18. 18. 14. Item Statistics
  19. 19. 15. Item Statistics (cont.)
  20. 20. 16. Improving the Original USC to improve the Stanford/UCLA study  Auto, Pharms, and groceries were removed  Smoothing effect  10-25 questions that delve deeper into issues
  21. 21. 17. Improved USC Model
  22. 22. 18. Autocorrelations
  23. 23. 19. Hours on the Internet
  24. 24. 20. Hours on Internet (cont.)
  25. 25. 21. Positive Correlations Positive correlation between hours spent on the Internet and amount of online purchases Significant deviation between males and females concerning when purchasing sporting goods
  26. 26. 22. Positive Correlations (cont.)
  27. 27. 23. Conclusion Stanford/UCLA Study  WebTV and InterSurvey Limitations  Extra Variables  Measured “strange” usage USC  Eliminated Unnecessary Variables  No WebTV InterSurvey Limitations  Hypothetical Correlations Have Value  More advanced Stage of Internet Use
  28. 28. 24. Questions? Questions?  Edgardo Donovan  Trident University  edonovan@tuiu.edu

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