Business Economics Online Business Growth

Question: Discuss about the Business Economics for Online Business Growth. Answer: Purpose The prime purpose of the research lies in the fact to understand the advanced education in the United States of America due to the recent growth of online universities and colleges across the country. The retention rate in percentage and the graduation rate in percentage would be studied for the data of the collected samples and it would give an idea about the pattern of higher education on these online colleges of the United States of America (Weiss and Weiss 2012). Background Higher education being one of the biggest challenges is being faced across the states of United States of America due to recent increase in the growth of the online universities. The independent organisation of Online Education Database aims to frame a complete list of recognized online colleges (Bickel and Lehmann 2012). They have collected data across 29 online universities of the United States of America for the variables the retention rate (%) and the graduation rate (%). The study if these two variables would give an idea about the higher education of the United States of America on their online colleges across the country. Method Data was collected for these purposes for the variables graduation rate and retention rate in these online universities. These collected data would undergo various statistical methods to study the scenario of the higher education in these online colleges. The statistical methods include descriptive analysis that consist of mean, standard deviation, minimum and maximum, scatter plot if the variable retention rate, regression analysis with graduation rate (%) as dependent variable and retention rate (%) as independent variable (Cohen et al. 2013). Results The result of the descriptive statistics for the variables retention rate and graduation rate is as follows: RR(%) Mean 57.41379 Median 60 Mode 51 Standard Error 4.315603 Standard Deviation 23.24023 Sample Variance 540.1084 Kurtosis 0.461757 Skewness -0.30992 Minimum 4 Maximum 100 Range 96 Sum 1665 Count 29 Largest(1) 100 Smallest(1) 4 Table 1: descriptive statistics of retention rate (Source: created by author) GR(%) Mean 41.75862 Median 39 Mode 36 Standard Deviation 9.865724 Sample Variance 97.33251 Standard Error 1.832019 Kurtosis -0.8824 Skewness 0.176364 Minimum 25 Maximum 61 Range 36 Sum 1211 Count 29 Largest(1) 61 Smallest(1) 25 Table 2: descriptive statistics of graduation rate (Source: created by author) The scatter plot with retention rate as independent variable is given below: Figure 1: Scatter plot with retention rate as independent variable (Source: created by author) The equation of regression to calculate the graduation rate (%) given the retention rate (%) is given by graduation rate = 25.4229 + 0.284526 * retention rate. The value of r square of this regression analysis is given by 0.449. Discussion The descriptive statistics of the variables RR (%) and GR (%) shows that the mean value of the variable RR (%) is 57.41379 while the mean value of the variable GR (%) is 41.75862. It is interpreted that the average rate of retention of the online universities in the United States of America is more than the average value of Graduation Rate (Bickel and Lehmann 2012). The retention rate is more than 50% and it can be stated the higher education in online universities is good for the students as they tend to study in these online colleges after completing their first year of education in the college. The graduation rate of the students of these colleges is not high. It can be interpreted that the students might not study properly in these online colleges or the education provided by these online colleges are not up to the mark to help the students complete their graduation. The standard deviation of the variable RR (%) is 23.24 while the standard deviation of the variable GR (%) is 9.86. It can be interpreted that the retention rates vary highly across the online colleges while the variation of the graduation rates across the online colleges of the United States of America is low. The value lowest value of RR (%) is 4 while the lowest value of GR (%) is 25 (Weiss and Weiss 2012). The highest value of RR (%) is 100 while the greatest value of GR (%) is 61. It shows that the range of retention across the online colleges is higher than the range of graduation. The scatter diagram indicates that the retention rate shows an upward trend in their values across the universities. The retention rate had also shows peak and trough in its motion which can be interpreted that the retention rate had increased for some colleges while it decreased for others (Kock 2013). The equation of regression which can be used to predict the graduation rate (%) when retention rate (%) is known is given by graduation rate = 4229 + 0.284526 * retention rate. The expected equation of regression is given by graduation rate = 4229 + 0.284526 * retention rate. The slope of the regression equation is 25.4229 while the value of the coefficient of retention rate is 0.2845 (Lauda?ski 2013). It can be interpreted that on absence of retention rate, the graduation rate would be 25.429 percent which is far less than the average graduation rate of the online colleges (Samuels et al. 2012). Thus, higher value of retention rate is important in order to have a higher value of graduation rate from these online colleges. The value of multiple r for the regression between retention rate and graduation rate is found to be 0.670245 (Oja 2012). This shows a strong correlation between the two variables graduation rate and retention rate. Thus, there is a strong statistically significant association between graduation rate and retention rate. The measure of r square was found to be 0.449228. It can be interpreted that the equation of regression did not provide a good fit for the data as the value of r square shows that the data are not closely fitted to the regression line (Harmatz and Greenblatt 2015). This is because the amount of r square is low. The percentage of retention rate of South University is 51% while its graduation rate is 25%. The value of retention rate of this college is higher than the average value of the rate of retention by the online universities across the United States of America (Cohen et al. 2013). The value of graduation rate of this college is lower than the graduation rate of the online universities across the United States of America. Thus, the students of this college tend to continue their studies after first year. However, the results of the students are not well in this college. The value of retention rate for University of Phoenix is 4 while the value of graduation rate is 28 (Lauda?ski 2013). Both the retention rate and graduation rate for this college is lower than the average values for the online colleges across the country. Thus, it can be interpreted that the education standard of this college is below the average standard of the education for online colleges across the country. Recommendation It is recommended that the online colleges should reframe their policies and strategies to build a better education system across the online colleges across the United States of America. They should also regularly check the colleges of their universities and help them to frame strategies so that they can increase their retention rate. It is also recommended that the online universities must reframe their syllabus and adapt better method of teachings their students. They should also amend their examination patterns so that the students can score better marks and increase the value of graduation rate. References Bickel, P.J. and Lehmann, E.L., 2012. Descriptive statistics for nonparametric models IV. Spread. InSelected Works of EL Lehmann(pp. 519-526). Springer US. Cohen, J., Cohen, P., West, S.G. and Aiken, L.S., 2013.Applied multiple regression/correlation analysis for the behavioral sciences. Routledge. Harmatz, J.S. and Greenblatt, D.J., 2015. Regression and Correlation.Clinical pharmacology in drug development,4(3), pp.161-162. Kock, N., 2013. Using WarpPLS in E-Collaboration Studies: Descriptive Statistics, Settings.Interdisciplinary Applications of Electronic Collaboration Approaches and Technologies,62. Lauda?ski, L.M., 2013. Regression versus Correlation. InBetween Certainty and Uncertainty(pp. 67-85). Springer Berlin Heidelberg. Oja, H., 2012. Descriptive statistics for nonparametric models. The impact of some Erich Lehmanns papers. 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