Online University Graduation and Retention Rates

This assignment analyzes the relationship between graduation and retention rates at online universities. It utilizes quantitative data from 29 institutions to assess the correlation between these two metrics. The analysis involves statistical tools like regression to determine the strength and direction of the relationship. Additionally, the study considers specific cases of South University and University of Phoenix to compare their graduation and retention rates with other online universities.

Economics and Quantitative Analysis

Table of Contents
Purpose...................................................................................................................................3
Background............................................................................................................................3
Method...................................................................................................................................3
Results....................................................................................................................................3
Discussion..............................................................................................................................5
Recommendations..................................................................................................................7
REFERENCES...........................................................................................................................8

Purpose
Now a day, high level of advancements takes place in the educational sector. Hence
traditional method of learning is replaced by online learning institutions to the significant
level (Topper and Lancaster, 2016). In this, aim of the present study is evaluate the extent to
which variables such as retention and graduation are associated with each other. On the basis
of such aim, following objectives has been framed by scholar is as under:
 To assess the trend of online learning institutions.
 To determine the impact of retention rate on graduation rate.
Background
In the present times, online universities are growing with the very high pace. The
rationale behind this, online colleges offer high level of convenience to the students in
comparison to the traditional or conventional way of learning. Online colleges offer
opportunity to the students to accomplish their study without following any strict time table.
This in turn helps individual in fulfilling the commitments of both family and work. In
addition to this, online courses are highly economical as compared to traditional methods.
Thus, financial downturn and low income is the major factor which has generated the
interested level of students toward online course curriculum (Permzadian and Credé, 2016).
The present report is based on the survey which has been conducted by scholar on the sample
of 29 colleges related to US. In this, report will describe the extent to which both the
variables such as retention and graduation rate are highly related each other.
Method
In the present report, quantitative tools and techniques have been employed by
scholars to determine suitable outcome from data gathered through 29 colleges of US. By
this, researcher has assessed the extent to which graduation and retention rate of online
colleges are highly associated with each other (Ridah and et.al., 2016). To determine the
suitable solution of research issue descriptive statistics and regression tool has been applied
by researcher. Through this, researcher has assessed the level to which graduation rate is
highly dependent on retention rate. Further, Pearson co-efficient correlation has also been
assessed by researcher to determine relationship which takes place between two variables.
Results

RR(%) GR(%)
Mean 57.41379 Mean 41.75862
Standard Error 4.315603 Standard Error 1.832019
Median 60 Median 39
Mode 51 Mode 36
Standard
Deviation 23.24023
Standard
Deviation 9.865724
Sample Variance 540.1084 Sample Variance 97.33251
Kurtosis 0.461757 Kurtosis -0.8824
Skewness -0.30992 Skewness 0.176364
Range 96 Range 36
Minimum 4 Minimum 25
Maximum 100 Maximum 61
Sum 1665 Sum 1211
Count 29 Count 29
Particulars Graduation rate Retention rate
Graduation rate 1 .67
Retention rate .67 1
Regression Statistics

Multiple R 0.670
R Square 0.449
Adjusted R Square 0.429
Standard error 7.46
Observation 29
ANOVA
df SS MS F
Significanc
e F
Regressio
n 1
1224.28
6
1224.28
6
22.0221
1 6.95E-05
Residual 27
1501.02
4 55.5935
Total 28 2725.31
Coeffic
ients
Standard
Error t Stat
P-
value
Lower
95%
Upper
95%
Lower
95.0%
Upper
95.0%
Intercep
t
25.422
9 3.746284
6.786
166
2.74E
-07
17.736
16
33.109
64
17.7361
6
33.1096
4
X
Variabl
e 1
0.2845
26 0.060631
4.692
772
6.95E
-05
0.1601
22
0.4089
3
0.16012
2 0.40893
Discussion
From descriptive statistics, it has been assessed that mean percentage of graduation
and retention is 41.76 and 57.41 respectively. Beside this, output of descriptive statistics
presents that retention rate of 50% of college’s accounts for 60. On the other side, median of
graduation rate is 39% which is below the level of average percentage. Further, mode of
retention and graduation rate is 51% and 36%. Hence, mode clearly presents such percentage
such figures have been generated by more colleges. Further, minimum and maximum value
of retention rate is 4% and 100%. It shows that there are several colleges who have generated
high retention rate by offering better educational and other facilities to the students (Padmore
and et.al., 2017). Besides this, there is one college out of 29 whose retention rate is highly
lower such as 4%. On the other side, minimum and maximum value of graduation rate
accounts for 25% and 61%. Standard deviation of both the variables is 23.24% and 9.8%
which shows that actual outcome will deviate from such figure in relation to the mean value.

Hence, online college institution needs to consider such aspects while framing strategic and
policy framework (Sutter and Paulson, 2017).
Scatter diagram: It is the most effectual statistical tool which displays the relationship
between two variables. Hence, such diagram clearly plots the relationship which takes place
between two variables. On the basis of this aspect, correlation can said to be positive when
dots slopes move from lower left to upper right and vice versa. Hence, by taking into
consideration the above diagram it can be said that moderate relationship takes place between
the two variables which are undertaken above. Hence, correlation measure such as .67
presents that retention and graduation rates are highly correlate with each other. Thus, if
retention rate will increase then graduate rate also influences in the similar direction. Hence,
both the variables have significant impact on each other. Along with this, by considering the
trend of scatter diagram it can be stated that liner relationship takes place between graduation
and retention rate.
Regression equation
On the basis of above mentioned table regression equation can be defined or interpreted in
the following way:
Y = a + bx + c
Y = Dependent variable
X = Independent variable (Regression equation, 2017)
Graduation rate = Intercept coefficient + coefficient of retention rate * retention rate
Graduation rate = 25.423 + 0.2845 * retention rate
The above mentioned equation is recognized as slope coefficient which in turn helps
in assessing or predicting the value of dependent variable on the basis of independent
measure. Hence, by keeping such aspect in mind researcher has identified the value of
graduation rate in accordance with retention rate.
H0: There is no significance different difference in the mean value of graduation and
retention rate.

H1: There is a significance different difference in the mean value of graduation and retention
rate.
In the present case situation value is below the level of 55% which in turn shows
failure in relation to goodness to fit. Due to this, regression equation cannot be interpreted in
an effectual way. Outcome of quantitative investigation presents that retention rate of 29
online universities is highly differs from each other. On the other side, graduate rate of such
online educational institutions are in line with each other. Hence, by assessing the whole data
set it has been identified that graduation and retention rates of students are moderately related
with each other.
By applying regression tool it has been assessed that R and R square of both the
variables are .67 & .44 respectively. Hence, .67 entails that there is significant positive an
moderate relationship between graduation and retention rates online universities. Further, R
square presents that if retention rate will change then graduation rate influences by .44. In
addition to this, adjusted R square is .429.
Cited case situation entails that graduation (GR) and retention rate (RR) of South
University is 25% & 51%. This aspect shows that 50% relationship takes place between such
two variables. Such aspect also presents that there is no comparison with other online
universities.
By making evaluation of gathered data set it has been assessed that RR and GR of
University of Phoenix accounts for 4% and 28%. It presents that both the rates which are
presented above not highly associated with each other. On the basis of this aspect, it can be
stated that the present University has relationship with other online institutions.
Recommendations
From such investigation, it has been assessed that graduation and retention rates of
online universities are moderately related with each other. Hence, there are several other
factors which have high level of influence on graduation rates. Further, by making use of
multiple regression analysis highly appropriate solution can be assessed.

REFERENCES
Books and Journals
Padmore, T. and et.al., 2017. Quantitative analysis of the role of fiber length on phagocytosis
and inflammatory response by alveolar macrophages. Biochimica et Biophysica Acta
(BBA)-General Subjects. 1861(2). pp.58-67.
Permzadian, V. and Credé, M., 2016. Do first-year seminars improve college grades and
retention? A quantitative review of their overall effectiveness and an examination of
moderators of effectiveness. Review of Educational Research. 86(1). pp.277-316.
Ridah, M. and et.al., 2016. Pyrosequencing-based quantitative identification of p16
methylation in diffuse large b-cell lymphoma at two centres in the east coast of
malaysia. Journal of Biomedical and Clinical Sciences. 1(1). pp.12-17.
Sutter, N. and Paulson, S., 2017. Predicting college students' intention to graduate: a test of
the theory of planned behavior. College Student Journal. 50(3). pp.409-421.
Topper, A. and Lancaster, S., 2016. Online graduate educational technology program: An
illuminative evaluation. Studies in Educational Evaluation. 51. pp.108-115.
Online
Regression equation. 2017. Online. Available through:
http://www.investorwords.com/4137/regression_equation.html
[Accessed on 3rd February 2017].