Impact Of Retention Rate On Graduation Rate In Online Colleges In The USA

Background

Describe the Economics and Quantitative Analysis?

In the last few years, the advanced education part in the USA has experienced through a critical change in its commercial center because of the pivotal development rate of online colleges. Despite the fact that certain development is there, regarding extent of graduation rate and also the extent of retention rate has essentially varied amid this timeline. It is for the most part considered that higher the retention rate implies the college will prove higher graduation rate. Under such circumstances, any change regarding retention rate and graduation rate ends up being a real sympathy toward the online colleges.

Presently, considering the latest economical trend pattern, it can be figured out that the associations are encountering ferocious contention, whether they are having a place in a tagged industry or stayed in distinctive industry. The revelry exists here predominantly as a result of the way that they expected to precede with a specific end goal further bolstering increase the competitive benefits.  Under such situations, there is a need of economic analysis thoroughly by the colleges that provide online education with the goal that they will get ready to comprehend the present pattern of the market with considering the two main considerations one is the retention rate and another is the graduation rate.

Compared to the conventional way of learning, there is a rapid growth of online education due to ease of accessibility. It empowers learners to be less bound by time and area and accordingly offers adaptability to individuals who are not ready to take after a strict timetable because of individual circumstances, family or work commitments. Separation instruction is regularly less lavish than conventional education. Nearly one-a large portion of foundations report that the financial downturn has expanded interest for up close and personal courses and projects.

• Three-quarters of organizations report that the financial downturn has expanded interest for online courses and projects.
• The financial effect on institutional plan has been blended; forty-seven percent have seen their funding abatement, however twenty-seven percent have encountered an increment.

Since, the retention rate essentially impact the extent of graduation rate in every colleges, it is essential to see such change in the both variables have any critical effect on the performance of the online colleges or not. Under such circumstances, this study is planned to evaluate this specific situation focused around these two variables and for that a samples of 29 online colleges in the United States were considered here. Data identified with these two variables is regarded in terms of percentage. Here, especially it is proposed to survey whether the impact of the retention rate over the graduation rate for chosen colleges is against the target populace should be been changed or not.

Based on the objective of the study that is to measure the impact of retention rate on the graduation rate for the chosen online universities, the use of statistical tool is the best way to find the result. Thus to make an effective conclusion of this study, the researcher uses the descriptive study method for finding the results of this study. Further, the researcher also utilizes the secondary data method based on both the variable which will be assessed utilizing the statistical tools. The reason behind utilizing the statistical tool for descriptive analysis is to make use of inferential statistical tool in a more effective way.

Research Methodology

The statistical tools that are used in analyzing this study are maximum, minimum, standard deviation and mean. Then the study follows an in depth inferential analysis using multiple regression models. One thing is to be noted that executing the statistical tool with regards to both inferential study or the descriptive study are like Excel, SPSS etc is used by the researcher. Here, the study primarily used the Microsoft Excel to do each count. In this manner, it can be said that the study takes after the beneath specified steps:

Step 1: Descriptive investigation of graduation rate and retention rate;

Step 2: Scatter graph of retention rate and graduation rate;

Step 3: For inferential study, multiple regression is used;

The underneath specified area gives subtle elements of the results found after the aforementioned three steps.

Retention Rate (%)	Graduation Rate (%)
Mean	57.41379	Mean	41.75862
Standard Deviation	23.24023	Standard Deviation	9.865724
Minimum	4	Minimum	25
Maximum	100	Maximum	61
Count	29	Count	29

Table 1: Descriptive statistics

Figure 1: Scatter diagram of retention rate and graduation rate

Regression Statistics
Multiple R	0.670
R Square	0.449
Adjusted R Square	0.429
Standard Error	7.456
Observations	29

Table 2: Regression statistics table

ANOVA
	df	SS	MS	F	Significance F
Regression	1	1224.286	1224.286	22.022	0.000
Residual	27	1501.024	55.593
Total	28	2725.310

Table 3: ANOVA table

	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%
Intercept	25.423	3.7463	6.7862	0.0000	17.7362	33.1096
X Variable 1	0.2845	0.0606	4.6928	0.0001	0.1601	0.4089

Table 4: Summary table

In this section, the researcher gives a detailed discussion of the result that is analyzed.

Referring to the table 1 as said above in the result area, it can be said that the table gives concise of the spellbinding insights identified with both the variables. From this table, the mean of maintenance rate is found as 57.41% and the mean of graduation rate is found as 41.76%. Since, the mean is the measure of focal propensity; it can be presumed that all the chose 29 colleges experienced more than 50 % maintenance rate, which implies well beyond 50% of the understudy who got affirmation in the separate colleges in a few courses, are staying with the colleges till end of their study.

Once more, the results specified in the table 1 likewise shows that the normal graduation rate of these chose college stay underneath the 50 %, which implies every year, the quantity of understudies who moved on from their individual colleges are lower than 50% of its understudy got affirmation in different condemnations.

In the event that the standard deviation is being considered as here, then it can be said that the standard deviation primarily investigates the deviation of data from its average value (). In this way, if the current connection is considered, then the results indicates in table 1 show that the maintenance rate of the chose colleges encounters more deviation in against the graduation rate of those colleges. This shows that maintenance rate varied more habitually than graduation rate.

From the results presented in the table 1, the minimum and the maximum value of the given data set can be identified. Hence, it can be concluded that the given set of data for the retention rate is greater than the spread of the graduation rate.  The minimum retention rate is estimated to be 4% and the maximum is 100%. The spread is significantly large and it is 96%. On the other side, its have been estimated that the maximum graduation rate has been estimated to be 61% and the minimum value of graduation rate is 25%. Hence, it can be stated that the spread of the variable is 36%. It can be stated that the retention rate is fluctuating almost double of the graduation rate. The table also support that results related to the standard deviations. According to the figure 1, which provides scatter diagram of graduation and the retention rate considering the retention rate as the independent variable demonstrated three important aspect such as direction, form and strength. In this case, the scatter diagram has been drawn in the above section considering the retention rate and graduation rate. In the following section, the scatter diagram is analyzed along with its implications.

• Direction

Results

It has been observed that there are two types of directions i.e. positive direction and negative direction which can be explained by discussing the direction of the scatter plot. In this case, the positive direction implies that the greater values of the category variable will be related with the higher value of the response variable. In the same manner, the negative direction occurs when the large value of category variable is associated with the lower value of the response variable. In the given situation, the large values of the category variable which indicates retention rate is associated with the large value of the respond variable which indicates the graduation rate. From the scatter diagram, it can be implied that the two variables are presenting a positive direction (XUE, 2010).

• Form

There are different forms of scatter diagrams. The different forms include no association among the variables, linear association, perfect linear association or no linear association among the variables. Analyzing the scatter diagram presented in this paper, it can be concluded that the two variables, i.e. graduation rate and retention rate has linear association (Montgomery, Peck and Vining, 2012).

• Strength

One of the important aspects of the scatter diagram is its strength. The strength of the scatter plot can be also categorized as no correlation between the variables, weak correlation, moderate correlation and strong correlation. In this case, the scatter plots between the graduation rate and retention rate demonstrates moderate correlation (Montgomery, Peck and Vining, 2012).

The regression equation that can be effective for evaluating the variables can be represented as:

Rate of Graduation = Intercept Coefficient + Coefficient of Retention Rate × Retention Rate

Therefore, if the results are followed then it can be observed that that coefficient of intercept is valued at 25.423 and retention ate coefficient is valued at 0.2845. Thus, the estimated regression that can be drawn from the results will be:

Graduation Rate = 25.423 + 0.2845 × Retention Rate

It is known that slope of a line is considered as a measurement that is used for measuring that how many number of units can go up or can go down in relation to each unit that moves to right. The general line slope value can be either, positive, negative or zero (Heuser et al. 2012). On the other hand, if slope is negative in relation to regression line then it may suggest that the correlation among week and entry price can be negative or vice versa. Therefore, the value of intercept in that case is 25.423. Thus, the intercept value is tells the graduation rate’s expected mean value whereas the retention rate is regarded as zero (Boden, 2011). Moreover, the coefficient of determination value is 0.449. It is considered as specific statistics that helps in presenting the information in context to goodness of fit in relation to regression model. Thus, it helps in providing complete knowledge about the effectiveness of regression line in showing the exact points.

According to the provided case, the goodness of fit represents the appropriateness of the model in determining the rate of graduation in context to provided retention rate (Heyneman, 2012). Thus, it can be computed from the study that any value that is close to 1 can provide better estimation. Apart from that, if the value relating to coefficient of determination move away from the value 1, then it can be written down that such estimated regression may not be appropriate or sufficient enough to give the right figure relating to graduation rate by considering retention rate. Moreover, it can be difficult to predict the rate of graduation in relation to retention rate (Hoyert et al. 2012).

Discussion

The retention rate and the rate of graduation can be associated with one another by a significant measurement which is the coefficient of determination or the goodness of fit.0.449 is the coefficient of determination in the present case. The appropriateness of the results becomes 44.9%. The regression equation cannot interpret the results and there is failure to provide goodness of fit as the value is below 55%.

 It is evident from the discussion above that the rate of retention deviates among the 29 online universities. The rate of graduation has shown similar results. Thus the provided data is not significant to determine the rate of graduation based on the rate of retention (Montgomery, Peck and Vining, 2012). This specific aspect has to be noted to draw the conclusion that there is moderate relationship between the rate of graduation and the rate of retention.

In case of South University it is seen that the rate of retention is 51% while the rate of graduation is 25%.Thus it can be said that the relationship between the two rates is 50%. Thus it can be said that there is no comparison with the online Universities.

The case of University of Phoenix shows that the rate of retention is 4% and the rate of graduation is 28%. There is not much significant association between the two rates. Thus the present University has relation between its performances with the online universities.

The study reveals moderate association between the rate of retention and the rate of graduation. The association is positive in nature. The equation of regression is not best fit. Other variables can influence the above rates. Multiple regression analysis will serve as a tool for the analysis.

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