## 2 Data and Methods
### Analytic Plan  
Our research consists of two steps. First, due to the large number of total questions within the two batteries, data was reduced using factor analysis. If several factors can be extracted to represent the twenty-one total independent variables, our analysis would be simplified. Second, we wish to gain a deeper understanding of how groups within the African American population differ. We do this using Classification and Regression Tree Analysis (CART). CART analysis is a non-parametric statistical procedure that produces sub-groupings of individuals who are homogeneous with respect to a dependent variable [28]. Researchers have used CART to categorize college alumni as potential donors [29]; recidivism in a prison population [30]; the academic achievement of first generation students [31]; African Americans most likely to buy a given technology [3], and in medical research where identifying high-risk sub-groups is critical to quality treatment [32; 33; 34]. There are several advantages to using CART which make it ideal for addressing the questions posed in this study. First and foremost, CART is a classification technique that predicts a dependent variable. CART allows us to directly address our research questions. For example, consider a situation where we are interested in a scalar dependent variable. Further, we have a series of categorical independent variables (race, ethnicity, age), that we would like to use as predictors of this scale. We want to answer the question: Which groups of people score the highest (or lowest) on this scale? We are not necessarily concerned with the net effects of race, ethnicity, or age as in regression analysis. Instead, we are \begin{table}
\begin{tabular}{|l|c|c|c|} \hline  & **No** & \
\begin{tabular}{c} **Yes, Not** \\ **Yesterday** \\ \end{tabular} &
\begin{tabular}{c} **Yes,** \\ **Yesterday** \\ \end{tabular} \\ \hline \multicolumn{4}{|c|}{**Basic Information Seeking**} \\ \hline \multicolumn{4}{|c|}{**Advanced Information Seeking**} \\ \hline \multicolumn{4}{|c|}{Send instant messages to someone who’s online at the same time} & 75.7 & 17.0 & 7.3 \\ \hline \multicolumn{4}{|c|}{Create or work on your own online journal or blog} & 92.7 & 4.7 & 2.7 \\ \hline \multicolumn{4}{|c|}{Read someone else’s online journal or blog} & 89.2 & 7.4 & 3.4 \\ \hline \multicolumn{4}{|c|}{Use a social networking site like MySpace, Facebook or LinkedIn.com} & 85.0 & 9.0 & 6.0 \\ \hline \multicolumn{4}{|c|}{Download a podcast so you can listen to it or view it later} & 88.4 & 9.8 & 1.8 \\ \hline \multicolumn{4}{|c|}{Watch video on a video-sharing site like YouTube or GoogleVideo} & 68.9 & 22.2 & 8.9 \\ \hline \multicolumn{4}{|c|}{Download or share files using peer-to-peer file-sharing networks, such as BitTorrent or LimeWire} & 91.5 & 7.0 & 1.5 \\ \hline \multicolumn{4}{|c|}{_Advanced Information Totals_} & 84.5 & 11.0 & 4.5 \\ \hline \multicolumn{4}{|c|}{**Social Networking**} \\ \hline \multicolumn{4}{|c|}{No} & Yes \\ \hline Make new friends & 93.0 & 7.0 & \\ \hline Stay in touch with friends & 87.4 & 12.6 & \\ \hline Flirt with someone & 97.2 & 2.8 & \\ \hline Make plans with your friends & 92.1 & 7.9 & \\ \hline Make new business or professional contacts & 95.9 & 4.1 & \\ \hline Promote yourself or your work & 96.0 & 4.0 & \\ \hline Organize with other people for an event, issue, or cause & 94.1 & 5.9 & \\ \hline \multicolumn{4}{|c|}{_Communication Totals_} & 93.7 & 6.3 & \\ \hline \end{tabular}
\end{table} 
Table 2: _Cont._concerned with the _gross_ effects of these variables--how they work together to influence a score on the scale. A classification tree answers this question by classifying cases according to combinations of dependent variables. CART _stratifies_ the population with respect to this scale, and is ideal for our research. For each scale we create with factor analysis, we can develop a hierarchy of groups within the African American population.