This dissertation project explores the potential for using an inferential statistics test (t-tests) within an existing writing program assessment design. The purpose of using inferential statistics is to provide several perspectives on a data set collected using the existing assessment design thereby improving what a writing program administrator can learn about the program. To demonstrate the use of statistical tests, I selected as a variable of interest participation in an international collaboration, the Trans-Atlantic and Pacific Project (TAPP). Based on this variable, I asked, can inferential statistics identify whether participation in TAPP created a difference in student portfolio scores for a program outcome? To perform the t-test, I calculated the mean portfolio scores for TAPP and for Non-TAPP groups. Then, after sorting the program data by course, two courses, a writing in the health professions and a writing in the technical professions, had enough sections participate in TAPP to conduct two more tests, one for each course. The tests posed the same question, whether participation in TAPP had a difference in portfolio scores for a program outcome, but had zoomed from the program level into the course level. The tests indicated that at the highest level (the program) participation in TAPP did not have a statistically significant difference on portfolio scores. The tests at the other level (the course) indicated that participation in TAPP did not have a statistically significant difference on writing in the health professions but did have a statistically significant difference on writing in the technical professions. Possible explanations for these results are examined in relation to existing writing studies literature. The approach of examining several levels is dubbed a zoomable assessment because the statistical tests allow for more nuanced examinations, that is, the tests zoom into the data set. Based on the findings, I propose further uses and possible limits of uses of inferential statistics as a complement to existing assessment designs. As part of the proposal, I advocate for assessment design, such as zoomable assessment, that is accessible, meaning the design does not require special software or extensive knowledge of advanced statistical analysis methods.