Internet Usage Statistical Data Analysis

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Internet Usage Statistical Data Analysis

Transcript of Internet Usage Statistical Data Analysis

Internet UsageStatistical DataAnalysis

Edgardo DonovanRES 610 – Dr. Joshua ShackmanModule 5 – Session Long Project

Monday, September 19, 2011

Overview 1. Study Background 2. Top/Lowest Uses 3. Top/Lowest Uses Chart 4. InterSurvey 5. Sampling Issues 5. Sampling Issues 6. Hypotheses 7. Case Processing 8. Reliability 9. Item Statistics 10. Item Statistics (cont.) 11. Summary Item Stats

Overview (cont.) 12. Inter-Item Correlations 13. More Quantitative Analysis 14. Item Statistics 15. Item Statistics (cont.) 16. Improving the Original 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.)

Overview (cont.) 23. Conclusion 24. Questions?

1. Study Background

2000 UCLA study surveying the digital future

Limited to WebTV users Initially started at Stanford, then UCLA, Initially started at Stanford, then UCLA,

then USC

2. Top/Lowest Uses

Top Uses: Learning Surfing (overlap?) Reading about products Reading about products

Surprising Lowest Uses: Schoolwordk Banking Job Search

3. Top/Lowest Uses Chart

4. InterSurvey

Relied upon a form application tool named “Intersurvey”

Survey had to be done online Low interest in effectively sampling the US Low interest in effectively sampling the US

Internet user population

5. Sampling Issues

WebTV Set Top Boxes Limited to low end income demographic

Poor attempt at sampling External validity problematic External validity problematic

6. Hypotheses

“Negative correlation between Internet and TV use

Negative correlation between Internet Use and traditional social activity and shoppingand traditional social activity and shopping

No insight on survey questions

7. Case Processing

Case Processing Summary

N %

Cases ValidCases Valid1241 100.0

Excludeda

0 .0

Total1241 100.0

a. Listwise deletion based on all variables in the procedure.

8. Reliability

Reliability Statistics

Cronbach's AlphaCronbach's Alpha Based on

Standardized Items N of Items

.816 .809 17

9. Item Statistics

10. Item Statistics (cont.)

11. Summary Item Stats

12. Inter-Item Correlations

13. More Quantitative Analysis

14. Item Statistics

15. Item Statistics (cont.)

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 10-25 questions that delve deeper into

issues

17. Improved USC Model

18. Autocorrelations

19. Hours on the Internet

20. Hours on Internet (cont.)

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 Significant deviation between males and females concerning when purchasing sporting goods

22. Positive Correlations (cont.)

23. Conclusion

Stanford/UCLA Study WebTV and InterSurvey Limitations Extra Variables Measured “strange” usage Measured “strange” usage

USC Eliminated Unnecessary Variables No WebTV InterSurvey Limitations Hypothetical Correlations Have Value More advanced Stage of Internet Use

24. Questions?

Questions?

Edgardo Donovan Trident University edonovan@tuiu.edu