You must follow the instructions below to get credits for this assignment.
Hint: Make sure to discuss study’s goal, subjects, and variables in the data.
The Early Childhood Longitudinal Study sought to measure the academic progress of more than 20,000 children ranging from kindergarten to fifth grade. The subjects were chosen from across the country to represent an accurate cross section of American schoolchildren. The study measured the students’ academic performance and gathered a variety of information, for example: his or her race, gender, family structure, socioeconomic status, the level of his or her parents’ education, and so on.
Hint: A correct answer must have a discussion on a main concept of regression, often called as, “all else being equal”, “controlling for other variables”, or “Ceteris paribus”. The author explained this concept using “the circuit board analogy”.
Regression analysis is a phenomenal statistical analysis method that allows you to examine the relationship between two or more variables of interest. It lets you sift through massive amounts of data by holding constant every variable except the two you wish to focus on, and then showing how those two co-vary.
Hint: A correct answer must have a discussion on causality versus correlation.
A regression analysis can demonstrate correlation, but it doesn’t prove causation. The analysis can’t answer questions posing the idea that X causes Y or vice versa. Instead it can show that those two correlate or don’t correlate. It is one of the few drawbacks of this analysis tool, I believe it is still extremely useful and would save hours of time sorting through your data searching for correlation.
Hint: See page 150.
The reading states, “Consider this fact: the ECLS data reveal that black students in good schools don’t lose ground to their white counterparts, and black students in good schools outperform whites in poor schools.” So according to the study, the quality of a child’s school does have a clear impact on their academic progress. It’s not so much about the test score gap as it is the quality of the school that hinders or helps the student further their education.
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”.
It would prove quite difficult to control for the quality of schools, a plethora of factors come into play when recording this data. It’s much harder to control a child’s influence outside of school versus inside. When they’re at school teachers could conduct studies that everyone can do, making a level playing field. When doing your analysis, you don’t need to include ALL the variables, just the key ones you need to find your answer.
After I finished the reading, I was pretty stunned. There are a huge amount of factors all being played into one study on schools. This is where regression analysis can save the day, it has the ability to disentangle very convoluted problems; Problems where the predictors seem meshed together and impossible to separate. This tool allows us to isolate certain variables we’re looking for and see if there is any correlation.
Hint: Use message, echo and results in the chunk options. Refer to the RMarkdown Reference Guide.