Hypothesis Testing - Ebola

Data analysis is an intersection of math and science as it requires the calculation, interpretation, and explanation of data. The successful conclusion of data analysis can be achieved through different means. For this post, analysis of a survey conducted among 103 pharmacy science students will require a t-test to compare data from a matched pair. The pharmacy science students completed a survey prior to and after an information session regarding Ebola. The analysis will look to determine if there was any significant changes in their answers following the information session. When conducting a survey, there are factors that cannot be controlled but may have an impact on the output. In the instance of this survey, the students are all in the same pharmacy science level, but there isn't any indication regarding their performance. Suppose, for example, that of the 103 students surveyed, 13 are top performers, 10 are above average, 70 are average, and 10 are below average. How does their academic ability and understanding impact their survey answers? Also, was the survey timed? Were all the students given the survey at the same time and in the same conditions? Were all the students in the same information session? Independent variables have to be considered when analyzing data because of the opportunity it creates to skew data. The dependent variables in this scenario would be the fact that all the students are answering the same question and are from the same program.
Here the survey data can be viewed with descriptive statistical analysis. Reviewing the TTest results and the standard deviation, the overall survey responses were not statistically different prior to and following the information session. Among the 103 students surveyed, questions 26 and 27 showed the greatest change in attitude based on the higher standard deviation. Interestingly, some students went from disagreeing to agreeing while others went the opposite direction. Considering the research question is to determine if the information session had any impact on the students knowledge or attitude, the data analysis would say it was unsuccessful. The low standard deviation for the questions indicate there wasn't a significant change in student answers following the session.