1. Questions re Internet Use How many/what percent use it How often, how much For what purposes From where (home, office, public-access computer) Differences –by geography, demographics, other characteristics of interest –Differences that require public policy intervention?

2. Reasons for Interest policy implications –Educational, economic effects of “digital divide” National International –Government mitigation? business implications

3. Assumptions Internet access is good –Educational effects –Employment effects –Other economic effects –Participation in society There are policy reasons for society as a whole, government to be concerned International issues: –Economic opportunity –Participation in global community –Democratizing effects

4. Our interest Survey-based social science research –Methods –Uses –Interpretation Key findings

5. A Nation Online, Feb., 2001 5th in a series measuring US digital divide Less emphasis on haves and have-nots parts to the study: –Computer use and internet use –Online activities –How and where people go online –Digital generation: young people –Digital workplace –People with disabilities –The unconnected –Reductions in inequality

6. Survey research Determine goals Design survey –Questionnaire –Sample, sampling method –Administration –Analysis Pretest Redesign Administer Code Edit Analyze data Interpret findings

7. Goals: Uses of survey research Demographics –Age, race, income, urban/rural, education… Behavior (self-reports) Opinions, perceptions

8. Some Limits of Surveys Reaching users is easier than non-users Relies on voluntary cooperation, possibly biasing the sample Questions have to be unambiguous, amenable to short answers You only get answers to the questions you ask; you generally don’t get explanations The longer or more complex the survey the less cooperation

9. Some alternatives Diary studies Critical incident techniques Monitoring, behavior tracking Experiments –HomeNet study gave people computers and tracked them over time –Validity problems?

10. Sampling

11. Sample design Probability samples –random –stratified random –cluster –Systematic –GOAL: Representative sample Non-probability sampling –convenience sampling –purposive sampling –quota sampling

12. Time Cross-sectional studies –Collect data now from experienced and new users –Assumes that the two groups differ mainly in experience, and conditions similar x time Cohort studies –Follow same population tho samples may differ; e.g. people who first used Internet in 1995; college grads from 1990 Panel studies –Follow same group over time –Track changes –However: People drop out

13. Administering Surveys Other-administered –Phone –In person Self-administered –Mail –Web –Paper in convenient place…

14. Active vs passive sampling active: solicit respondents –Send out email –Phone –Otherwise reach out to them –Follow up on non-respondents if possible passive – e.g. on web site –Response rate may be unmeasurable –heavy users may be over-represented –Disgruntled and/or happy users over-represented

15. Response Rates low rates may > bias –Whom did you miss? Why? How much is enough? –Babbie: 50% is adequate; 70% is very good May help if they understand purpose –Don’t underestimate altruism Incentives may increase response –Reporting back to respondents as a way of getting response

16. A Nation Online Sample, p. 92 [Universe – US residents] population –US residents age 3+ during week of September 16-22, 2001 sample –CPS survey sample from 1990 decennial census, updated for new construction –sampling unit: households –size: 57,000 households units of analysis –Households 57,000 –Individuals age 3+: 137,259 Survey administration: have to go to CPS to find out: phone or in person Respondent: a person >= 15 years old knowledgeable about everyone in household

17. Variables Dependent, Independent Conceptualization Operationalization

18. Definitions/Operationalization A Nation Online: –Individuals age 3+ –“Is there a computer or laptop in this household?” –“Does anyone in this household connect to the Internet from home?” –“Other than a computer or laptop, does anyone in this household have some other device with which they can access the Internet, such as: – cellular phone or pager – a personal digital assistant or handheld device –a TV-based Internet device –something else/ specify” Sept. 2001: 143,000,000 Nielsen//NetRatings –“Internet usage estimates are based on a sample of households that have access to the Internet and use the following platforms: Windows 95/98/NT, and MacOS 8 or higher” –“The Nielsen//NetRatings Internet universe is defined as all members (2 years of age or older) of U.S. households which currently have access to the Internet.” –Sept. 2001: 168,600,000 (+18%)

19. Questionnaire construction: Questions Ordering Wording

20. Error “All statistics are subject to sampling error, as well as non-sampling error such as survey design flaws, respondent classification and reporting errors, data processing mistakes and undercoverage. The Census Bureau has taken steps to minimize errors in the form of quality control and edit procedures to reduce errors made by respondents, coders, and interviewers.” p. 92 The Census Bureau determined that some of the data were statistically insignificant for meaningful analysis because the sample from which they were derived was too small.

21. Sampling error A sample statistic is an estimate of a population parameter Table 1-1: Internet use by % of state population – 90% confidence interval (the chances are 90% that the true value falls in this range) –U.S.: 53.6 – 54.1 –California: 50.0 – 53.3 –South Carolina: 44.6 – 50.7 Size of confidence interval a function of –Sample size (NOT population size) –Distribution of sample results Overlapping confidence intervals = not statistically significant difference –Davis 52% +- 3% –Simon 48% +- 3%