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The DOE conductued a study on Early Childhood in the 1990s. They studied over 20,000 children between kindergarten and 5th grade. The DOE did this to measure students acedemic performance as it realates to their upbringing, social status, and economic status.
Regression is a form of decifering large sets of data piece by piece. It is different from correlation because correlation is the study of only two variables. Regression allows the user to compare many different data bits and pieces and determine wether or not they are correlated.
A major drawback of regression analysis is that it does not proove cause. It can proove correlation however there is a possibility that the cause of the correlation can sometimes be many different things or multiple things.
Students in bad schools tend to lose ground to students in better schools. The ECLS data, while seemingly dated, claims that black students in good schools dont lose ground to their white counterparts. And vise versa.
Hint: For this question, you may need additional information in addition to the assigned reading. You may Google search someting like “how does regression control for variables”.
A good way to control the quality of the schools of the dataset would be to look at their history and label them properly. You might want to take data for rate of dropouts and super-seniors aswell as data for early graduations and rate of students moving onto higher educations.
Regression can be an extremely useful tool for collecting complicated data.
Hint: Use message, echo and results in the chunk options. Refer to the RMarkdown Reference Guide.
thankyou for the extra time MR. Lee