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Summary

A correlation may be defined as the relationship between two variables. It is represented by a number. "The correlation is one of the most common and most useful statistics." (Correlation, 2006). Correlation helps to analyze whether two variables are related and it also helps to determine the extend of their relationship with each other… - Subject: Miscellaneous
- Type: Essay
- Level: College
- Pages: 3 (750 words)
- Downloads: 0
- Author: dachcullen

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- Tags:
- Carrion Comfort
- Classrooms
- Comfort
- Correlation
- Effective Use
- Facilities
- Jonathan
- Jonathan Kozol
- Lunch
- Variable

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A negative correlation means that the changes in the variables are not uniform. In other words, when one variable increases the other decreases and vice versa.

The correlation between different variable are in different cases are analyzed here. This analysis basically relates to the internet subsidies in Public Schools. "Policymakers and analysts have argued that public schools are a natural place to teach underserved populations about computers and increase access to new technology." (Goolsbee & Guryan, 2003).

The correlation between the variable A and variable B of school lunch program can be seen first. The variable A is the number of students who are eligible for school lunch. The variable B is the amount of funding received by the school. Different types of correlation can occur between these two variables. A positive correlation between the two variables means that adequate funds are received by the school in order to provide lunch for the students at the school. This refers to the proper working of the system. A negative correlation between the two variables means that even though there are adequate numbers of students eligible for the lunch, the schools don't receive the necessary fund for providing the students with proper lunch. The third case is where the correlation between the two variables is minimal. This is rather a neutral case where the condition is that there are no eligible students and funds are not required by the schools.

Correlation between subsidy and age of students

There is a positive, negative and neutral correlation between the subsidy and age of students. Here the variable A is the impact of subsidy and variable B is the age of students at school. A positive correlation between these two variables means that the subsidy received by the school contains the students who satisfy the eligibility age for it. A negative correlation between these two variables means that even though the schools receive subsidy it does not actually satisfy the age criteria for availing the benefits. This means that the fund is directed not to the required area. Similarly a minimal correlation means that the schools don't satisfy the criteria only to certain extend and so they are not able to avail the benefits of the subsidy.

Correlation between classrooms and student performance

The intention behind connecting classrooms with the latest internet facility is to ensure better performance of the students. In this case the variable A is the number of classrooms connected with internet. The variable B is the performance of the students in the test conducted. The correlations between these two variables are very much relevant because the actual results of the spending are understood by this. A positive correlation means that the classrooms are connected with better internet facilities and the students are provided the most modern internet facilities in the classrooms and the performance level of the students is very higher in the test. This shows that the nation has benefited by investment in facilities. A negative correlation means the classrooms are connected with internet and the students does not show sufficient improvement in their performance. This is a failure. A minimal correlation means that there are neither internet facili ...Download file to see next pagesRead More

The correlation between different variable are in different cases are analyzed here. This analysis basically relates to the internet subsidies in Public Schools. "Policymakers and analysts have argued that public schools are a natural place to teach underserved populations about computers and increase access to new technology." (Goolsbee & Guryan, 2003).

The correlation between the variable A and variable B of school lunch program can be seen first. The variable A is the number of students who are eligible for school lunch. The variable B is the amount of funding received by the school. Different types of correlation can occur between these two variables. A positive correlation between the two variables means that adequate funds are received by the school in order to provide lunch for the students at the school. This refers to the proper working of the system. A negative correlation between the two variables means that even though there are adequate numbers of students eligible for the lunch, the schools don't receive the necessary fund for providing the students with proper lunch. The third case is where the correlation between the two variables is minimal. This is rather a neutral case where the condition is that there are no eligible students and funds are not required by the schools.

Correlation between subsidy and age of students

There is a positive, negative and neutral correlation between the subsidy and age of students. Here the variable A is the impact of subsidy and variable B is the age of students at school. A positive correlation between these two variables means that the subsidy received by the school contains the students who satisfy the eligibility age for it. A negative correlation between these two variables means that even though the schools receive subsidy it does not actually satisfy the age criteria for availing the benefits. This means that the fund is directed not to the required area. Similarly a minimal correlation means that the schools don't satisfy the criteria only to certain extend and so they are not able to avail the benefits of the subsidy.

Correlation between classrooms and student performance

The intention behind connecting classrooms with the latest internet facility is to ensure better performance of the students. In this case the variable A is the number of classrooms connected with internet. The variable B is the performance of the students in the test conducted. The correlations between these two variables are very much relevant because the actual results of the spending are understood by this. A positive correlation means that the classrooms are connected with better internet facilities and the students are provided the most modern internet facilities in the classrooms and the performance level of the students is very higher in the test. This shows that the nation has benefited by investment in facilities. A negative correlation means the classrooms are connected with internet and the students does not show sufficient improvement in their performance. This is a failure. A minimal correlation means that there are neither internet facili ...Download file to see next pagesRead More

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