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Economic: Online Colleges Or Universities Are Made To Offer Training Add in library

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Question:

Background One of the biggest challenges in the higher education sector has been the recent growth of online universities. The Online Education Database is an independent organisation whose mission is to build a comprehensive list of accredited online colleges. The Excel spreadsheet (OnlineEdu.xlsx) contains data on the retention rate (%) and the graduation rate (%) for 29 online colleges in the United States.
Instructions
(a) Provide a descriptive analysis of the two variables (e.g., mean, standard deviation, minimum and maximum).
(b) Develop a scatter diagram with retention rate as the independent variable. 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 regression 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 your university compared to other online universities?
(h) Suppose you were the president of the University of Phoenix. After reviewing the results, would you have any concerns about the performance of your university compared to other online universities?
Your report needs to be structured as follows:
(1) Purpose
(2) Background
(3) Method
(4) Results
(5) Discussion
(6) Recommendations.
 

Answer:

(1) Purpose:

Online colleges or universities are made to offer training to the understudies who can't be display physically in the customary setting, for example, classroom. It has a point of a substantial scale intelligent interest and open access through or through web and other system innovations. Presently a day this methodology of learning or instruction is expanding. The broad utilization of machines and web has made the methodology of learning or instruction through online college quicker and less demanding. These are putting forth a full educational program as same as a typical college, yet as of late there is disaffirm between online college and the ordinary college. The online training database is an autonomous association whose mission is to construct a complete rundown certifies online universities (Welfens and Walther-Klaus, 2007). The motivation behind Retention rate is to screen or see in drawing in and holding understudies for the colleges. Retention rate is ascertained by net wage of the college less profits isolated by Net Pay or Income. Development Rate is the rate of increment of the quantity of understudies of the colleges. Presently I am going to investigate between the retention rate and development rate of the online universities in USA.

 

(2) Background:

In higher studies are confronting disaffirm to pick school or colleges. Which school would it be a good idea for them to pick Online College or ordinary University? Lately understudies are picking online college rather than ordinary college. So there is showing up a greatest test in advanced education part has been late development of online colleges. So we need to investigate the development rate and retention rate of the online colleges in USA.

 

(3) Technique or Method:

For this examination we are making mean, minimum value, maximum value and standard deviation of the retention rate and advancement rate of the online universities or colleges of USA. Besides we are also using regression scientific explanation through graduation rate and retention rate (Mccraw, 2012). After that we are discovering the backslide co capable and measurably find the centrality between graduation rate and retention rate.

 

(4) Results:

As showed by the giving data set or surpass desires gave, we adequately circles or figure the conclusions. The outcomes are measured by the aid of some acceptable examination like mean, standard deviation, minimum value and maximum value using some item like Microsoft Office (MS- Excel). The giving data set of the syntheses furthermore its retention rate and graduation rate are in rate is shown in underneath by the help 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 information about the retention rate of online schools or colleges in USA we are going to make a scatter graph by tolerating the upkeep rate and advancement rate as free variable. As showed by the giving data set the most maximum value, minimum value, standard deviation and mean are exhibited in underneath by the aid 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 handling by the help of Microsoft Office or MS- Excel and its significant comparison or equation.

Where, mean estimation of the Retention Rate is proportionate to total entire of the Retention Rate in rate (%) separated by the total no of online schools like 57.414 and moreover mean estimation of the Graduation Rate is equal to total aggregate of the Graduation Rate in rate (%) differentiated by the total no of online universities like 41.759

Correspondingly, the standard deviation is measured by σ= √((σ (x-µ)^2)/(N-1)) or

 

Where, σ = the standard deviation

x = each one estimation of the information set

µ = the mean quality

N = the quantity of qualities or size of the information set

By the help of the above comparison or equation we will viably measured or learn the standard deviation of the retention rate is 23.2402 and furthermore the standard deviation of graduation rate is 9.8657

Quickly are making a scatter chart by taking under considered improvement rate and retention rate of the schools or colleges of USA is sown in below.

From the spread diagram or disseminate graph we can see that advancement rate and support rate are bury related. If improvement rate will extend then support rate will moreover assemble. The rate of both retention and advancement are upward climbing.

The method of basic least square is giving guarantee that gage the backslide line which is moreover the best fitting line, has been drawn from the given data (Drennan, 2002). Here in the above scatter plot the plot does not seem to lie close to the line. So we can say that the backslide line or the best fitting line will fit in amazingly well.

Right away we are making an once-over yield or conclusions of regression measurements by an assumption. 

SUMMARY OUTPUT

Regression Statistics

Multiple R

0.621627987

R Square

0.386421354

Adjusted R Square

0.362822175

Standard Error

17.1688846

Observations

28

 In a matter of seconds we are making a normal regression scientific statement proclamation and interpreting the coefficient inclination or incline. To do this we have expect the qualities. In the followings we have survey backslide 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 below table we are put on display the different regression and staying of df, SS, MS, F and Significance of F. we are furthermore giving their total. 

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 graph 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 going hand in hand with we are showing the observations, predication 7 and leftover/ residual in the below table from 1-28 different variables or components. 

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

 

(5) Discussion:

From the given data we have learned the regression scientific explanation. Translation or Interpretation of Coefficient as a change of rate of Y is situated up of as a change in the prohibitive mean of Y. There is no need of taking assurance breaks for coefficients into records. When we evaluate or deciphered a regression coefficient adequately as a rate of advancement of a prohibitive mean which is rather than a change in given two variables. It is all that much crucial to take into under thought the weakness in the estimation of the regression coefficient. As indicated by this procedure I have discovered the backslide numerical proclamation line. Which are y= 1.860x + 29.51 and y= 1.143x + 24.60. Of course I have taken a 95% assurance between time for the inclination or slant. The rate of advancement of the prohibitive mean of Y concerning x is evaluated to be some place around 1.860 and 1.143 is regularly attractive over saying; the rate of advancement of the unforeseen mean of Y with respect to x is close around 2 or more. The understanding of the coefficient of which is not genuinely gigantic. This kind of interpretations is frequently made shockingly (Canadian economy online, 2006). If the regression coefficient of t test is not measurably discriminating, this won't be the suitable to interpret or evaluate the coefficient. There is no accurately tremendous immediate which dependence of the mean of Y on x was perceived. In the translation or interpretation of coefficients in the various regressions with the same tongue or variable is in a broad sense used as a piece of single immediate regression.

As demonstrated by the giving data set or exceed expectations sheet the retention rate estimation of the South University is much higher than valuation for the graduation rate regard. The retention rate regard in rate of the South University is 51% and the graduation rate estimation of the South College is only 25%. Thusly, the retention rate estimation of the South University is 26% more than the graduation rate regard. This is exhibited that the improvement of the school, which is moreover associated with the advancement of the college furthermore when the retention rate quality is extension than backslide rate estimation of the South University is in like manner augmentation. We unmistakably said that the retention rate estimation of the South University is moreover particularly with respect to the regression rate regarded (Ryan and Others, 2010). Hence backslide examination of the South University is incredible fit furthermore the improvement rate and the advancement of the South University is augmentation. Thusly, the amounts of the understudies are moreover augments and also the school is similarly offered some new stream or learning task for some new understudies. In this manner it is clearly said that the retention rate regard when addition than the arrangement of activity is in advantage.

 

According to the giving data set or exceed expectations sheet the support rate estimation of the University of Phoenix is much lower than deference of the graduation rate regard. The retention rate regard in rate of the University of Phoenix is only 04% and also the graduation rate estimation of the University of Phoenix is 28%. In like manner, the graduation rate estimation of the University of Phoenix is 24% more than the retention rate regard. The retention rate worth is exhibited that the advancement of the school, which is similarly associated with the improvement of the university or college furthermore when the retention rate quality is development than the regression rate estimation of the University of Phoenix is also increase however in University of Phoenix the graduation rate quality is extensions and more than the retention rate regard. Hence the regression correlation of the University of Phoenix is terrible fit and furthermore the improvement rate and the advancement of the University of Phoenix is reduction. Consequently, the amounts of the understudies are moreover reduces furthermore the school is completed not offered some new stream or learning framework for some new understudies. Likewise it is unmistakably said that the graduation rate regard when addition than the arrangement of activity is in hardship.

 

(6) Recommendation or Suggestion:

As per the above detailed analysis we will effortlessly measure some unmistakable examination like mean, standard deviation, minimum as well as maximum values and also regression estimations of some online colleges, which are additionally talked about in above. The retention rate esteem and the graduation rate estimation of the online colleges are additionally given in rate (%). By the assistance of the retention rate worth and graduation rate esteem we will likewise discover or measures the regression estimations of the online colleges (Levy, 2009). The regression estimations of the online colleges are likewise talks about in above. The regression estimations of the online colleges are likewise demonstrated the development of the online colleges like augmentations of the understudies, expanding the learning project and a few others, which is additionally related to the net benefit of the colleges or plan of action.

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. Baltimore: Johns Hopkins University Press.

Kerrigan Snyder, B. (2013). The unemployed college graduate's survival guide. Avon, Mass.: Adams Media.

Levy, B. (2009). Town born. Philadelphia: University of Pennsylvania Press.

McCraw, T. (2012). The Founders and Finance. Cambridge, Mass.: Belknap Press of Harvard University Press.

Miller, N. (2010). Botanical aspects of environment and economy at Gordion, Turkey. Philadelphia: University of Pennsylvania Museum of Archaeology and Anthropology.

Quarter, J., Mook, L. and Ryan, S. (2010). Researching the social economy. Toronto [Ont.]: University of Toronto Press.

The informal economy: underground economy, moonlighting, subcontracting, household economy, unorganized sector, barter, ghetto economy, second economy: a research guide. (1992). Choice Reviews Online, 29(07), pp.29-3647-29-3647.

The new economy. (2003). Choice Reviews Online, 41(04), pp.41-2279-41-2279.

Welfens, P. and Walther-Klaus, E. (2007). Digital excellence. Berlin: Springer
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