Scatter Diagram Indicate About the Relationship Between the Two Varia

Question - (a) Provide a descriptive analysis of the two varaiables(e.g.,mean,standard deviation, minimum and maximum).(b). Develop a scatter diagram with retention rate as the independentvariable. What does the scatter diagram indicate about the relationship between the two variables?(c). Develop and estimate a regression equation that can be used to predict the graduation rate(%) given the retention rate(%). (d). State the estimated regressio equation and interpret the meaning of the slope coefficient.(e). Is there a statistically significant association between graduation rate (%) and retention rate (%). What is your conclusion?(f). Did the regression equation provide a good fit? Explain.(g). Suppose you were the president of South University. After reviewing the results, would you have any concerns about the performance of tour unicersity compared to other online universities?(h) Suppose you were the president of the University of Phoenix. After reviewing the reults, would you have any converns about the performance of your university compared to other online universities? Answer- Purpose Online schools or colleges are made to offer preparing to the understudies who can't be show physically in the standard setting, for instance, classroom. It has a state of a generous scale canny investment and open get to through or through web and other framework developments. Shortly a day this system of learning or guideline is extending. The wide use of machines and web has made the approach of learning or guideline through online school faster and less requesting. These are advancing a full instructive program as same as an average school, yet starting late there is disaffirm between online school and the customary school. The internet preparing database is an independent affiliation whose mission is to develop a complete summary guarantees online colleges (Drennan, 2002). The inspiration driving Maintenance rate is to screen or see in attracting and holding understudies for the universities. Support rate is found out by net pay of the school less benefits confined by Net Pay or Income. Advancement Rate is the rate of augmentation of the amount of understudies of the universities. Shortly I am going to research between the upkeep rate and advancement rate of the online colleges in USA. Background Recently understudies are picking online school as opposed to conventional school. So there is showing up a most noteworthy test in progressive training part has been late advancement of online universities. So we have to explore the improvement rate and upkeep rate of the online schools in USA. Technique or Method: For this investigation we are making mean, greatest, least and standard deviation of the retention rate and development rate of the online colleges or universities of USA. Furthermore we are additionally utilizing regression mathematical statement through graduation rate and retention rate (McCraw, 2012). After that we are ascertaining the relapse co proficient and measurably find the centrality between graduation rate and retention rate. Results: As indicated by the giving information set or exceed expectations gave, we effectively disks or figure the conclusions or yields. The results or the yields are measured by the assistance of some clear investigation like mean, standard deviation, least or minimum and maximum utilizing some product like Microsoft Office (MS- Excel). The giving information set of the compositions and also its retention rate and graduation rate are in rate is indicated in beneath by the assistance of table. College Retention Rate in percentage (%) Graduation Rate in percentage (%) Western International University 7 25 South University 51 25 University of Phoenix 4 28 American InterContinental University 29 32 Franklin University 33 33 Devry University 47 33 Tiffin University 63 34 Post University 45 36 Peirce College 60 36 Everest University 62 36 Upper Iowa University 67 36 Dickinson State University 65 37 Western Governors University 78 37 Kaplan University 75 38 Salem International University 54 39 Ashford University 45 41 ITT Technical Institute 38 44 Berkeley College 51 45 Grand Canyon University 69 46 Nova Southeastern University 60 47 Westwood College 37 48 Everglades University 63 50 Liberty University 73 51 LeTourneau University 78 52 Rasmussen College 48 53 Keiser University 95 55 Herzing College 68 56 National University 100 57 Florida National College 100 61 From the given data about the retention rate of online colleges or universities in USA we are going to make a disperse chart by accepting the maintenance rate and development rate as free variable. As indicated by the giving information set the maximum value, minimum value, standard deviation and mean are demonstrated in beneath by the assistance of the table. Minimum 4 25 Maximum 100 61 Mean 57.41379 41.75862 Standard Deviation 23.24023 9.865724 The above table is measured or tackling by the assistance of Microsoft Excel or MS- Excel and its valuable equation or formula. Where, mean estimation of the Retention Rate is equivalent to aggregate whole of the Retention Rate in rate (%) isolated by the aggregate no of online colleges like 57.414 and in addition mean estimation of the Graduation Rate is equivalent to aggregate entirety of the Graduation Rate in rate (%) separated by the aggregate no of online colleges like 41.759 Correspondingly, the standard deviation is measured by = (( (x-)^2)/(N-1)) or= (( (x-)^2)/(N-1)) Where, = the standard deviation x = each one estimation of the information set = the mean quality N = the quantity of qualities or size of the information set By the assistance of the above equation or formula we will effectively measured or ascertain the standard deviation of the retention rate is 23.2402 and in addition the standard deviation of graduation rate is 9.8657 Presently are making a disperse graph by taking under thought of development rate and retention rate of the colleges or universities of USA. From the disseminate outline or scatter diagram we can see that development rate and maintenance rate are entomb related. On the off chance that development rate will expand then maintenance rate will likewise build. The rate of both retention and development are upward climbing. The procedure of common minimum square is giving ensure that gauge the relapse line which is additionally the best fitting line, has been drawn from the given information (Kerrigan Snyder, 2013). Here in the above disperse outline the plot does not appear to lie near to the line. So we can say that the relapse line or the best fitting line will fit in extremely well. Presently we are making a rundown yield or outcomes of regression statistics by a presumption. SUMMARY OUTPUT Regression Statistics Multiple R 0.621627987 R Square 0.386421354 Adjusted R Square 0.362822175 Standard Error 17.1688846 Observations 28 Presently we are making an expected regression mathematical expression statement and deciphering the coefficient slant or slope. To do this we have expect the qualities. In the followings we have assess relapse and remaining. Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept -0.427733114 15.09197951 -0.02834175 0.97760601 -31.44974098 30.59427475 -31.44974098 30.59427475 25 1.408074644 0.34797141 4.046523943 0.000414052 0.692809173 2.123340114 0.692809173 2.123340114 In the underneath table we are demonstrating the distinctive relapse and remaining of df, SS, MS, F and significance of F. we are additionally giving their aggregate. ANOVA df SS MS F Significance F Regression 1 4826.678724 4826.678724 16.37435602 0.000414052 Residual 26 7664.035561 294.7705985 Total 27 12490.71429 In the followings there is a diagram of coefficients, standard error, t-Stat, P-value, lower and upper rates in percentage. Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept -0.427733114 15.09197951 -0.02834175 0.97760601 -31.44974098 30.59427475 -31.44974098 30.59427475 25 1.408074644 0.34797141 4.046523943 0.000414052 0.692809173 2.123340114 0.692809173 2.123340114 In the accompanying we are demonstrating the perceptions, predication 7 and residual in the underneath table from 1-28 separate variables or factors. RESIDUAL OUTPUT Observation Predicted 7 Residuals 1 34.77413297 16.22586703 2 38.9983569 -34.9983569 3 44.63065548 -15.63065548 4 46.03873012 -13.03873012 5 46.03873012 0.961269879 6 47.44680476 15.55319524 7 50.26295405 -5.262954052 8 50.26295405 9.737045948 9 50.26295405 11.73704595 10 50.26295405 16.73704595 11 51.6710287 13.3289713 12 51.6710287 26.3289713 13 53.07910334 21.92089666 14 54.48717798 -0.487177983 15 57.30332727 -12.30332727 16 61.5275512 -23.5275512 17 62.93562584 -11.93562584 18 64.34370049 4.656299513 19 65.75177513 -5.751775131 20 67.15984977 -30.15984977 21 69.97599906 -6.975999061 22 71.3840737 1.615926295 23 72.79214835 5.207851652 24 74.20022299 -26.20022299 25 77.01637228 17.98362772 26 78.42444692 -10.42444692 27 79.83252157 20.16747843 28 85.46482014 14.53517986 Discussion: From the given information we have ascertained the regression mathematical statement. Interpretation or Translation of Coefficient as a change of rate of Y is set up of as a change in the restrictive mean of Y. There is no need of taking certainty interims for coefficients into records. When we assess or deciphered a regression coefficient effectively as a rate of progress of a restrictive mean which is as opposed to a change in given two variables. It is all that much essential to take into under thought the vulnerability in the estimation of the regression coefficient. According to this technique I have ascertained the relapse mathematical statement line. Which are y= 1.860x + 29.51 and y= 1.143x + 24.60. Then again I have taken a 95% certainty interim for the slant or slope. The rate of progress of the restrictive mean of Y concerning x is assessed to be somewhere around 1.860 and 1.143 is normally desirable over saying; the rate of progress of the contingent mean of Y regarding x is close around 2 or more. The understanding of the coefficient of which is not factually huge. This sort of translations is regularly made shockingly (Welfens and Walther-Klaus, 2007). On the off chance that the regression coefficient of t test is not measurably critical, this won't be the suitable to decipher or assess the coefficient. There is no factually huge direct which reliance of the mean of Y on x was recognized. In the interpretation or translation of coefficients in the numerous regressions with the same dialect or variable is fundamentally utilized as a part of single direct regression. As indicated by the giving information set or excel sheet the retention rate estimation of the South University is much higher than appreciation of the graduation rate esteem. The retention rate esteem in rate of the South University is 51% and the graduation rate estimation of the South University is just 25%. Consequently, the retention rate estimation of the South University is 26% more than the graduation rate esteem. This is demonstrated that the development of the college, which is additionally connected to the development of the university and also when the retention rate quality is expansion than the relapse rate estimation of the South University is likewise increment. We unmistakably said that the retention rate estimation of the South University is additionally specifically relative to the regression rate esteem. Henceforth the relapse comparison of the South University is great fit and also the development rate and the development of the South University is increment. Alo ng these lines, the quantities of the understudies are likewise increments and additionally the college is likewise offered some new stream or learning project for some new understudies (Levy, 2009). Subsequently it is obviously said that the retention rate esteem when increment than the plan of action is in benefit. As per the giving information set or excel sheet the maintenance rate estimation of the University of Phoenix is much lower than admiration of the graduation rate esteem. The retention rate esteem in rate of the University of Phoenix is just 04% and in addition the graduation rate estimation of the University of Phoenix is 28%. Accordingly, the graduation rate estimation of the University of Phoenix is 24% more than the retention rate esteem. The retention rate worth is demonstrated that the development of the college, which is likewise connected to the development of the university and also when the retention rate quality is expansion than the regression rate estimation of the University of Phoenix is additionally increment however in University of Phoenix the graduation rate quality is expansions and more than the retention rate esteem. Consequently the regression comparison of the University of Phoenix is bad fit and additionally the development rate and the development of the Uni versity of Phoenix is abatement. Hence, the quantities of the understudies are likewise diminishes and also the college is carried out not offered some new stream or learning system for some new understudies. Accordingly it is unmistakably said that the graduation rate esteem when increment than the plan of action is in misfortune. Recommendation or Suggestion: According to the above point by point investigation we will smoothly measure some unmistakable examination like mean, standard deviation, least and in addition most extreme qualities furthermore relapse estimations of some online universities, which are moreover discussed in above. The maintenance rate regard and the graduation rate estimation of the online schools are also given in rate (%). By the aid of the maintenance rate worth and graduation rate regard we will in like manner find or measures the backslide estimations of the online universities (Ryan and Others, 2010). The relapse estimations of the online schools are in like manner discusses in above. The relapse estimations of the online universities are moreover showed the improvement of the online schools like expansions of the understudies, growing the learning task and a couple of others, which is also identified with the net advantage of the universities or arrangement of activity. References Anderson, K., Cockburn, J. and Martin, W. (2009). Would freeing up world trade reduce poverty and inequality?. Adelaide: Centre for International Economic Studies. Canadian economy online. (2005). Choice Reviews Online, 42(12), pp.42Sup-0465-42Sup-0465. Canadian economy online. (2006). Choice Reviews Online, 43(12), pp.43Sup-0519-43Sup-0519. Drennan, M. (2002). The information economy and American cities. 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