The results in this report are based on data from a series of telephone interviews conducted by Princeton Survey Research Associates International between October, 2004, and June, 2005. For results based on the sample of 6,403 adults, 18 and older, conducted January-June, 2005, one can say with 95% confidence that the error attributable to sampling and other random effects is plus or minus 1 percentage point. For results based adult internet users (n=4,207), the margin of sampling error is plus or minus 2 percentage points. For results based on the sample of teens (ages 12 to 17), conducted in October-November, 2004, (n=1,100), the margin of error is plus or minus 3 percentage points. For results based on teen internet users (n=971), the margin of error is plus or minus 4 percentage points. Some questions were asked in only one recent survey and therefore have a higher margin of sampling error, as noted in the table on page 3. The table includes analysis of subgroups of internet users that also have a higher margin of error. Below is a list of the average margin of error for each age group listed in the table:
- The average margin of error for internet users ages 18-28 is ± 7% across all surveys.
- The average margin of error for internet users ages 29-40 is ± 6% across all surveys.
- The average margin of error for internet users ages 41-50 is ± 6% across all surveys.
- The average margin of error for internet users ages 51-59 is ± 7% across all surveys.
- The average margin of error for internet users ages 60-69 is ± 9% across all surveys.
- The average margin of error for internet users ages 70+ is ± 11% across all surveys.
For more information about the latest trends in internet use, please see https://www.pewinternet.org/Trend-Data.aspx.
For more information about the sample of 12- to 17-year-olds, please see the “Teens and Technology” report (available at https://www.pewinternet.org/Reports/2005/Teens-and-Technology.aspx).
In addition to sampling error, question wording and practical difficulties in conducting telephone surveys may introduce some error or bias into the findings of opinion polls.
The sample for this survey is a random digit sample of telephone numbers selected from telephone exchanges in the continental United States. The random digit aspect of the sample is used to avoid “listing” bias and provides representation of both listed and unlisted numbers (including not-yet-listed numbers). The design of the sample achieves this representation by random generation of the last two digits of telephone numbers selected on the basis of their area code, telephone exchange, and bank number.
New sample was released daily and was kept in the field for at least five days. The sample was released in replicates, which are representative subsamples of the larger population. This ensures that complete call procedures were followed for the entire sample. At least 10 attempts were made to complete an interview at sampled households. The calls were staggered over times of day and days of the week to maximize the chances of making contact with a potential respondent. Each household received at least one daytime call in an attempt to find someone at home. In each contacted household, interviewers asked to speak with the youngest male currently at home. If no male was available, interviewers asked to speak with the oldest female at home. This systematic respondent selection technique has been shown to produce samples that closely mirror the population in terms of age and gender. All interviews completed on any given day were considered to be the final sample for that day.
Non-response in telephone interviews produces some known biases in survey-derived estimates because participation tends to vary for different subgroups of the population, and these subgroups are likely to vary also on questions of substantive interest. In order to compensate for these known biases, the sample data are weighted in analysis. The demographic weighting parameters are derived from a special analysis of the most recently available Census Bureau’s Annual Social and Economic Supplement (March 2004). This analysis produces population parameters for the demographic characteristics of adults age 18 or older, living in households that contain a telephone. These parameters are then compared with the sample characteristics to construct sample weights. The weights are derived using an iterative technique that simultaneously balances the distribution of all weighting parameters.