The Correlation Between Attendance Patterns and Math Scores - Dissertation Example

Correlation is the linear relationship that defines two succinct variables, and the coefficient is the measure or relationship between the two variables expressed in a numerical term. In the present study, the main variables to consider as correlates are 'attendance' and 'achievement' in the subject of mathematics. The value of such a correlation coefficient lies somewhere between the integers of +1 and -1 which are positive and negative coefficients respectively, and they both represent a perfect positive or negative coefficient.

That is, a coefficient of -1 is a perfect negative correlation and +1 is a perfect positive correlation. Phrased in different terms, if an analysis produces either coefficient there is a conclusive relationship defined by the coefficients in question, which means that a value of 0 means that there is no relationship in question. The correlates being examined in this analysis, already have a well-documented 'correlation', however, a more concise expression of this relationship in terms of establishing a coefficient, has not to be determined for the correlates as they pertain to the level of grade 10 in the State of New York.

That is, while both attendance in school and attendance in mathematics has a positive correlation, the same cannot be said about high school students in the State of New York, even though an inference can be made that says that because this occurs in both other grades and subjects along with mathematics, that it can be induced or inferred that it would occur as a positive correlation in grade 10 mathematics students in New York. The correlations would include other variables that have been identified in the literature review.

Those are the variables that have been documented that go along with either academic achievement or absenteeism. These would include variables like gender, race or rather an ethnicity, socio-economic group, distance from the school, types of support systems.