The Analysis of Southwestern University

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To begin with, it should be stated that the case study is dedicated to the Southwestern University, which is regarded to be an independent, selective university of liberal arts. The study is held in accordance with the general practices, associated with the forecasting model creation, and analysis of the general accounting practice. Originally, it should be stated that the forecasting model, which is intended for the present study is based on the average results of the previous years, and with the consideration of the dynamics of the changes in the amounts

Forecasting Model

The forecasting model which is selected for the current analysis is the regression data analysis, intended for the calculation of the incoming data of the attendance rates, and providing the forecasted data on the basis of the percentage analysis and the dynamics of the changes, observed during the previous years. (Bassett, 2004) Actually, this data analysis tool is unable to take into consideration the additional factors, which will be discussed in the Options part of the paper.

The attendance rates were analyzed in accordance with the regression analysis forecasting method. The data on the matters of Southwestern University, which requires analysis, is forecasted on the following graph:

Attendance rates

Originally, the data on the attendance rate, provided on the initial database, represents the tendency of the changes within the rates of the incoming data.

The choice of this method is reasoned by the fact that regression analysis forecasting is regarded to be the most precise and effective statistical analysis tool. The particular attention should be paid to the r-square value: originally, this is the analysis tool of the initial variables, which represents the dependence of the dynamics on the incoming data. Thus, if this rate is 0.8 and higher, the forecast is regarded to be positive. The rate of the current analysis is 0.82, thus, the rate will be regarded positive for sufficiently long period of the forecasted tendency and projected attendance. In accordance with Nersesian (2004, p. 391) the following statement should be emphasized:

To explore such issues, the investigator assembles data on the underlying variables of interest and employs regression to estimate the quantitative effect of the causal variables upon the variable that they influence. The investigator also typically assesses the “statistical significance” of the estimated relationships, that is, the degree of confidence that the true relationship is close to the estimated relationship.

The predicted variable for the 2009 attendance project is 2441.5. Originally, this number confirms the r-square rate tendency for the positive forecasted dynamics of the provided data, and the further changes of the dynamics.

Revenues Expected in 2008 and 2009

The rate of the revenues and changes, which should be expected in 2008 and 2009 are generally represented in the analysis results. Thus, the predicted variable column, which represents the forecasts in accordance with the predicted tendencies and rates of the change dynamics, reveals the rates and values of the projected revenues.

Observation Predicted Variable Residual
2002 164736,3 9463,72
2003 164818,6 12081,43
2004 164900,9 27699,15
2005 164983,1 -164781
2006 165065,4 51534,58
2007 165147,7 63952,29
2008 200457,7 3952,47
2009 243317,4 6534,332

In accordance with the provided table, the projected revenues will be 200457.7 and 243317.4 correspondingly. Thus, these data do not fit the general tendencies, as in spite of the positive dynamics in general, the particular revenues appear to be negative, as the incoming data represent the variables, which are performed in accordance with the statistical analysis and forecasts. The only statement that should be emphasized from the perspective of this notion is the concept of the half-positive tendency. Originally, it was described by Pearson and Bracker (2001), and they emphasize that such tendencies are possible if the initial data is either provided without the required accuracy, or the dynamics of the changes, which represent the allover tendency can not reveal the actual necessity of the incoming data, as well as the accuracy of the r-square rate, described in the previous part of the paper.

The School’s Options

As for the matters of options, which should be discussed in this part of the paper, there is strong necessity to emphasize that SWU, as the largest university of liberal arts and the state college in Stephenville, Texas, entails close to 20,000 students. Originally, the options of the university entail not only resident students, but also students from the other cities. Heizer and Render (2007, p. 145) emphasize the following statement on the matters of Southwestern University:

Always a football powerhouse, SWU is usually in the top 20 in College football rankings. Since the legendary Bo Pitterno was hired as its head coach in 1999 (in hopes of reaching the elusive number 1 ranking), attendance at the five Saturday home games each year increased. Prior to Pitterno’s arrival, attendance generally averaged 25,000 to 29,000 per game. Season ticket sales bumped up by 10,000 Just with the announcement of the new coach’s arrival. Stephenville and SWU were ready to move to the big time.

Taking into consideration the popularity of the football, there is strong necessity to emphasize the fact that there is an issue, which faces the issue of the absence of NCAA ranking. Moreover, the existing stadium, which was built in 1953, has seating for only 54,000 fans. The tendencies for the increase of the attendance rates may cause the further reconstruction of the stadium, thus, the forecasted rates may differ from the real attendance rates. Thus, the calculation error may become larger. In the light of the fact that the stadium is not included into the NCAA ranking reveals the fact that initial incoming data may be wrong, as precise registering of the attendance is impossible without this ranking.

Another statement that should be emphasized on the matters of the school options relates with demands upon joining SWU with the rest of the university league. Originally, if this decision is taken, it will require the reconstruction of the existing stadium, o building a new one. The fact is that, the increase of the attendance rates makes this problem actual enough for implementing the required decisions on the matters of improving the conditions for the players and visitors of the stadium. On the one hand, the increase of the comfort will attract additional audience, while joining of the leagues will distract some opponents of this decision. Anyway, the administration of the stadium has sought for a revenue projection, presuming an average ticket price of $20 in 2006 and a 5% increase each year in future prices. (Heizer and Render, 2007)


Finally, it should be emphasized that the analysis, provided in the paper is based on a regression analysis of the incoming data, and the rate of the change dynamics may be used for the forecast of the further rates of attendance of the stadium. Nevertheless, there are numerous factors and options, which may influence the real results, thus the error should be taken into consideration.


Bassett, G (2004) “Operations Management for Service Industries Competing in the Service Era” Quorum Books, Westport, CT.

Heizer, J. Render, B (2007) “Operations Management” Pearson Prentice Hall.

Nersesian, R. (2004) “Trends and Tools for Operations Management an Updated Guide for Executives and Managers” Quorum Books Westport, London.

Pearson, J., Bracker, J. (2001) “Operations Management Activities of Small, High Growth Electronics Firms” Journal of Small Business Management. Vol., 28, No., 1. p.20.

Spearin, C. (2006) “Special Operations Forces a Strategic Resource: Public and Private Divides” Parameters. Vol. 36, No. 4, p. 58.

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