just would like someone to read this and let me know what you think if it? does my point get across?

For my Simple Linear Regression Project, I chose to investigate the relationship between the average household income of a family for each state in the United States and compare that to the average graduation rate per state to see how strong the relationship between the variables is. The significance of this research could provide further insight into how economical issues modern day parents deal with can be affecting future generations who will be entering the workforce. A high school diploma is one of the first steps for many young adults to further their education in college or technical school and provides a large advantage while job hunting over those without a diploma. As housing, rent, groceries, and day to day costs go up every year and the minimum wage across the country could be as low as $7.25, it is vital we prepare our youth for the future to give them the best chance of success.

It is common knowledge that private schools are one way that a family's income level can result in a better education, which led me to further research into whether income has a direct impact on success in education. In "Public School vs. Private School: The Pros and Cons" the anonymous author mentions some of the benefits associated with attending private schools such as smaller classrooms, better one on one education with teachers and a more challenging curriculum for students. Attending these schools and academies however carries a large price tag, opposed to public schools which are far cheaper than private school to attend and must accommodate a large demographic of students such as disabled students and students with learning disabilities. Since private schools are not owned or operated by the government, the data available about them on the internet is scarce compared to public schools, and the information may be skewed due to smaller sample size and potential bias from the academies releasing information to favor them. Due to this, I chose to keep my sample focused on the public schools in the United States since the information is provided by the federal government itself. Originally, I was looking to use average ACT scores per state, but since the usage of SAT and ACT tests in each state vary greatly, graduation rates were chosen instead as they appear to be less volatile.

VARIABLES-

The variables used in this project are the average household income per state as my independent variable and the high school graduation rates as my dependent variable. My categorical variable are the 50 states in the United States. Information on all these variables came from worldpopulationreview.com, which is a reliable website based in the US with their data coming from the National Center for Education Statistics. The NCES gets their data directly from the Department of Education and is a part of the federal government.

PREVIOUS STUDIES-

Research prior to this project being conducted have shown that poverty has a large influence on the success of the average student. In 2009, the National Center for Education Statistics reported that children whose families are in the bottom 20% of all family incomes were five times more likely to drop out than the top 20% of families. Poverty has also been associated with other stressors such as hunger, domestic violence, and drug abuse in the family. Referred to as "toxic stressors", these negatively affect children and increase the odds of students showing signs of chronic absenteeism, disruptive behavior, and a low drive for achievement.

The National Dropout Prevention Center, a non-profit organization seeking to provide information to educators and students to increase graduation rates since 1986 provided information regarding dropouts and the struggles they go through. One investigation showcased on their website conducted by the Bureau of Justice in 2003 says that 75% of prison inmates are high school dropouts, and teen girls in the bottom 20% of the income bracket are five times as likely to become mothers than teen girls in the top 20%. These examples show that the relation between poverty and dropout rates is well researched and has been provided ample results to show a correlation between the two.

DATA BREAKDOWN

After gathering the data for both the 2022 graduation rates and the 2022 average household income, I created a boxplot with the information to get an idea of the distribution. The mean graduation rate for the states is 89.6% and the median is 90%. From looking at the five number summary, we can see the IQR is more skewed to Q1, while the IQR is about 5%. Next, I created histograms for both variables to see if there were observable similarities between the two. Both have a negative kurtosis, but the graduation rate has a negative skewness while average household income has a positive skew. The average household income is distributed more to the left of the curve while graduation rates are more scattered and weighted to the right.

After that, I made my fitted line plot. The R=.268 and the R^2=.072, or 7.2%. This shows that the independent variable, the average household income is not explaining a lot of the variation in the dependent variable, the high school graduation rate. The correlation coefficient for my data is .268, which is lower than the critical value of .279 for n=50 at a 95% confidence level. Since it is lower, the results are not statistically significant and there is not enough evidence on correlation according to this sample.

The regression equation I came up with was y=.8502+0.000001(x). Regarding the other results obtained from the research, I do not think it should be used for predictive purposes, as the data does not support correlation between the two variables. A reason the research could have had a large difference between the previous studies done on the topic could be because the sample size used is vast and varies too greatly and does not account for the other socioeconomic factors that could influence graduation rates in each state. Public schools must accommodate all students, and the difference between the top performing students and the bottom performing students is immense, as the bottom end could suffer from learning disabilities such as ADHD, ADD or autism or have stressors in their personal life such as abuse, neglect, and a weak support network.

CONCLUSION

While there is a provable relation between poverty and poor performance in school, the data used for this experiment do not provide enough evidence to support correlation between average household income and high school graduation rates. If this research was to be repeated, perhaps viewing another measurement of income for families would yield different results. The data itself is correct, but the outcome does not meet expectations. The original prediction for the project was that there would be a strong correlation between the two variables. Also, each state could have their own laws and policies that influence dropout rates, which could explain some of the outliers such as Wisconsin and Wyoming being among the lowest in average household income but having higher graduation rates than Maryland and Massachusetts, which are among the higher income households. This topic warrants further research in the future.