Analysis of Retention Rate and Graduation Rate in Online Universities

ECONOMICS AND QUANTITATIVE ANALYSIS
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ECONOMICS AND QUANTITATIVE ANALYSIS
Purpose
The online education has gain popularity during the last decade or so and led to significant
number of students availing these courses. As a result, it makes sense to analyse if the
performance of the online universities for which the given task focuses on two measures in
the form of RR% (Retention Rate) and GR% (Graduation Rate). Collectively these two are
pivotal factors that highlight the extent of drop-outs highlighted in the online universities in
US. This is pivotal as higher drop outs reflect potential issues that would need to be sorted in
the long run through pragmatic recommendations.
Background
The large scale internet penetration has altered the ecosystem related to product and service
delivery. Using internet as the medium, it became possible to transmit the various services to
far flung corners and avail these in the comfort of chosen location. Education also witnessed
significant changes owing to the growth in online courses which over the time have become
popular. This does not come as a surprise considering the benefits in the form of lower costs,
increased convenience, better time management and flexibility in time and geography for
availing various courses (Lederman, 2018). One key downside of these courses that has been
indicated through various empirical evidence is the high rate of dropout that are experienced
(Wellman, 2018). In order to ensure that these courses make a significant positive
contribution to education and economic development, it is pivotal that the issue of dropouts
must be kept within check.
Method
The sample data provided which contains information about RR% and GR% for a set of 29
online US universities acts as the pivotal first step. Using measures of central tendency along
with dispersion measures, descriptive statistics are represented that indicate the summary of
the sample data. Further, a scatter plot has been drawn to explore the level of association
between RR% and GR%. In order to carry out a detailed analysis on the same, regression
analysis is carried out based on Excel. Besides, inferential statistical techniques such as
hypothesis testing have been used to ascertain the statistical significance of slope and linear
relationship.
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ECONOMICS AND QUANTITATIVE ANALYSIS
Results
a) The descriptive statistics for the same data are presented below.
b) The scatter plot has been drawn using Excel and illustrated below.
The first noteworthy aspect is the arrangement of scatter points which exhibit an upward
trend which hints at the positive relationship between the two variables under consideration.
Further, the position of the scatter points is that the deviation of these points from the
regression line is not high which implies that association is strong in strength. This is
confirmed from the computation of correlation coefficient which comes out as 0.67 (Hillier,
2016).
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