Organization of This Report

The remainder of this report provides some additional details about participation as of the second year of Program implementation. Section 2 focuses on the DC private schools that offered to accept scholarship students during the first and second years of implementation. Section 3 updates the number of students that applied to and were awarded scholarships as part of the Program, including the subset of applicants who are the focus of the upcoming impact analysis.

For this report, which is descriptive, as well as for the later impact analysis reports, we will use several tests for calculating statistical significance, or the level of confidence that evaluators have that a difference between groups did not occur merely by chance. For most of the comparisons that we make, we use the "Student's t test." The t test is commonly used when the factor being considered, such as test scores, tends to be distributed continuously on a normal, bell-shaped curve. Unlike some significance tests, the t test incorporates information about the distribution of values in both comparison groups, and not just the overall population, and thus is a more precise measure of statistical significance than the Z test, for example.⁹ When the characteristic in question is not normally distributed—such as gender, which is an either/or and not a more-or-less—we use the "chi-squared" test of statistical significance. All group differences that are mentioned in this report are statistically significant at least beyond the traditional 95% confidence level using a two-tailed statistical test.