Association between Retention Rate and Graduation Rate in Online Universities

Economics and quantitative analysis
Name:
Institution:
9th February 2019

Purpose
The purpose of this study is to Conduct a simple linear regression analysis to examine the
association between the ‘retention rate’ (the independent variable) and the ‘graduation rate’ (the
dependent variable). We utilize data from the Online Education Database which is an
independent organization whose mission is to build a comprehensive list of accredited online
colleges.
Background
Different analysts have associated educational accomplishment and achievements with student'
persistence in campus, and these two components clarified effects from most other understudy
foundation properties. The association between retention and graduation should be a major
concern to the economists because it serves as an advantage to the growth of economy in three
key ways. First is because of the well-known structure of salary and employment that is
associated with various education levels. The second reason is the less well known but very
crucial relationship that exists between parents’ educational status and the chances that their
children will graduate. Lastly is the huge scholarly increase experienced by college graduates
eventually end up contributing to the economic and civic growth of our country (Penrose, 2012).
All these factors are very crucial to the growth of any economy hence it is a major concern for
the economists to be interested in the issue of retention and graduation (Ting, 2010).
Method
A sample of 30 universities was collected to investigate whether there is association between
retention rate and graduation rate. The hypothesis that this study sought to test is;
H0: There is no significant relationship between retention rate and graduation rate

HA: There is significant relationship between retention rate and graduation rate
To test the above hypothesis, the study performed both Pearson Correlation test and regression
analysis test in order to identify the relationship that exists if any.
For the regression analysis, the study sought to fit a regression model that would attempt to
predict the graduation rate based on the retention rate. The model that we sought to fit is;
Y = β0 + β1 ( X ) +ε
Where
Y =Graduationrate , X=Retentionrate , β0=Intercept ( constant ) coefficent , β1=Coefficientforretentionrate ∧ ε =e
Results
Descriptive analysis
Table 1 below gives the descriptive statistics for the two variables. As can be seen, the average
retention rate for the sampled universities was found to be 57.41% with an average graduation
rate of 41.76%. The median retention rate was 60% with the most frequent retention rate (mode)
reported across the 30 universities being 51%. The skewness values for both the retention rate
and the graduation rate shows that the two variables are close to being normally distributed since
the skewness values were either less than 0.5 or greater than -0.5 and closer to zero.
Table 1: Descriptive (summary) statistics
RR(%) GR(%)
Mean 57.41 41.76
Standard Error 4.32 1.83
Median 60.00 39.00
Mode 51.00 36.00
Standard Deviation 23.24 9.87
Sample Variance 540.11 97.33
Kurtosis 0.46 -0.88