When trying to compare two sets of data on a more statistical level in Excel, one must refer to the t-test. The t-test is used to determine whether or not data is statistically significant or if there is an accidental error. In other terms, we are testing to find out whether the null hypothesis is supported. Using the data from my last blog, I tested whether or not ethnicity plays a role in reading scores.
To determine whether or not the null is supported, one must look at "P(T<=t) one-tail." When looking at this if the P value is less than .5 than the null is rejected. If the P value is greater than .5 than the data failed to reject the null, meaning it is less than 95 percent significant.
To test my data, I compared three different ethnicities. For the first test, I compared white students reading scores to black students reading scores. When looking at the image you will see that the P value is less than .5, meaning the null was rejected. In simply terms, the data is statistically significant and there is no error.
For the second comparison, I compared white students reading scores against hispanic students reading scores. When looking at the image you will see that the P value is less than .5, meaning the null was rejected. In simply terms, the data is statistically significant and there is no error.
The third comparison, I compared hispanic students reading scores against black students reading scores. When looking at the image, you will see that the P value is less than .5, meaning the null was rejected. In simply terms, the data is statistically significant and there is no error.
Overall, the null was rejected, there is a 95 percent chance that is the students retook the reading test, the students scores would be very similar, meaning, the data is reliable. Because the null was rejected, the data shows that ethnicity plays a role in the reading test scores.
If I were to use this data and write an academic paper in APA format, I would compare the different ethnicities and the reading results. I would show each P value and explain what each P value meant. I would also show my data in a table or chart for a visual.
When using the t-test function, I did not have any difficulties. I thoroughly enjoy learning new uses for Excel. The possibilities are endless. I could use this in my classroom to compare students whether it be based on gender, ethnicity, etc.
When using this feature in Excel you are following ISTE NETS-3, Model Digital-Age Work and Learning, primarily focusing on communicating information to students, parents and colleagues as well as analyzing and evaluating data.