Hypothesis Testing

Today we learned how to formulate and test a hypothesis by using the tools in our Excel tools data pack.  People often look at data to create decisions.  As I have mentioned in previous posts, you have to be careful entering data into your model.  Today, we are looking to see that we are making correct correlations in data that we are analyzing.   In our sample, we looked at data that suggested  females read at a greater level than males in the 8th grade.  By using a T-Test, we are able to discern whether this data is statistically significant or likely a measurement error. The T-test basically measures the edges of a bell curve.  The larger or "thicker" the edges of the bell curve, the more likely a chance of measurement error or in other words, reproducing the same results using the same test.  We decided to test a 95% confidence level which is acceptable for education research.  This means that we are at least 95% certain that are assumptions are not due to measurement error.  For our exercise we compared the scores of our Black, White and Hispanic 8th grade readers.  We found that all our data was NOT due to measurement error

T Test Results

This project is most closely related to ISTE-2  design and develop digital learning experiences and assessments.  We learned how to assess data which could lead us to best classroom practices.