Excel 2

Wow. OK - this activity was not so easy for me. By the time I was finished, my mind was swimming with p's and t's and all sorts of statistics jargon. I think I ended up working through this correctly but translating the information from Dr. Pierce's Jing demonstration to my Mac version of Excel was a little confusing. I finally resorted to using this online tool to verify the answers that I came up with in Excel.

As a reminder, this activity focuses around answering this research question: Does student's gender impact 4th grade math performance? Our hypothesis is that there is a difference. We are looking for an indication of whether the differences we can see in the data are statistically significant or not. Our null hypothesis is that there is no difference. If our t test p value is less than .05 then we will reject the null hypothesis; if our t test p value is greater than .05 then we will not reject the null hypothesis.

Here is a graphic of my Excel results:









When I used the online tool at studentsttest.com I got the same results. If you want to see a screengrab from those tests, the one tailed test result is here and the two tailed test result is here.

Based on the discussion above and noting the one tailed p value of 2.51, I find that we will not reject the null hypothesis. In other words, although there is a difference between the male and female groups, that difference is likely related to error or chance.

As a prospective teacher, I can imagine using this sort of analysis with my future students. For the purposes of this discussion, let's assume I am teaching a high school history class. One topic I would like to investigate is the performance of students who take my class in the morning as compared to the performance of the students who take the class in the afternoon.

My research question would be the following: Is there a difference in educational performance between students who take my history class before noon and the educational performance of those who take the class in the afternoon. There would be two groups in this study: morning students and afternoon students. The dependent variable is that they are all taking the same class. The independent variable is the time of day when they take my class. My hypothesis would be that students who take my class in the morning perform at a higher level than those students who take my class in the afternoon. The null hypothesis would be that there is no significant difference in performance between morning and afternoon students and that any perceived difference is likely due to error or chance.

Relationship to Standards - the Excel 2 activity relates well to the following standards: 3(d) in that the use of Excel and statistical analysis models the effective use of current and emerging digital tools to analyze and evaluate information to support research and learning; 5(c) the use of Excel and statistical analysis allows educators to evaluate and reflect on current research and to make use of emerging digital tools; and 5(d) the use of Excel and statistical analysis allows educators to contribute to the effectiveness and vitality of the teaching profession.