The Opening Chapters Of Anita Saterlees Organizational...

The opening chapters of Anita Saterlee’s Organizational Management Leadership: A Christian Perspective introduce several business concepts that have been researched throughout the years. An examination of these concepts reveal not all are similar and there is no one perfect leadership style. Instead, the differences in leadership styles and management techniques, Satterlee argues, should be based upon the type of work and organization in which the leader or manager is engaged (Satterlee, 2013). Despite the transition inherent in the evolution of management theories, discussed in Chapters 1 and 2, the concepts of Followership, Transformational Leadership, and Maslow’s Hierarchy of Needs are timeless. The purpose of this report is to show that an in depth study and examination into these three concepts are beneficial to all who desire to manage and lead in any environment, in any field, and in any era. Followership as a Precursor to Leadership Anita Satterlee makes an obvious, but profound observation stating, â€Å"A leader cannot lead without followers (Satterlee, pg. 6, 2013).† Essentially, a leader without subordinates who are engaged can not lead properly. While this concept is easy to comprehend, what is most intriguing is Satterlee’s claim that â€Å"by mastering the role of followership, a subordinate prepares for the role of leadership (Satterlee, pg. 7, 2013).† Instead of viewing leaders as being static, it is important to view the process of leadership as more

Learning Is Viewed As One Of The Most Important...

Learning Theory Paper Kimberlyn Boddie EDUC 2130: Teaching Learning Professor: George Darden November 1, 2015 Learning is viewed as one of the most important interactive activities in which children engage. Although most learning occurs outside of the school setting, it is the heart of the educational process. Psychologists and philosophers searched to understand the true nature of learning, why and how learning occurs at different stages in life and how it can have an influence through teaching methods and similar endeavors. For many years, various learning theories have been listed as suggestions and these theories differ with understandable reasons. Whether theories are based on scientific evidence or†¦show more content†¦As a child, Dewey excelled as a student in public schools, then went on to study philosophy; graduating second in his class. While teaching at the universities, Dewey became fascinated with philosophical treatises and decided to expand focus in studying psychology and philosophy at John Hopkins. Although Dewey’s philosophical treatises were inspired by William James; George Sylvester Morris (American educator and philosopher) and G. Stanley Hall (American educator and psychologist) were among some of the the most influential philosophers in Dewey’s life. John Dewey and education- his ideas embodied the philosophy of pragmatism. His philosophy is known as instrumentalism, experimentalism and focus on the human experience; abandoning previous rigid exposure of transcendentalism through academia. He believed behavior is out of habit and change will produce unexpected outcomes. By creatively thinking, one can resume control of a shifting environment and through those thoughts, a connection with the real world is formed. A universal education is the best practice for teaching abandonment of habits and think creatively. Dewey’s approach to learning is that of hands-on learning, oppose to conforming to a lectured approach., education should stem from the principle of learning

Economics and Quantitative Analysis Retention Rate and Graduation Rat

Question: Describe the Economics and Quantitative Analysis? Answer: PURPOSE OF THE STUDY 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. BACKGROUND OF THE STUDY 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. METHODOLOGY 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. 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. OUTCOME Calculation of descriptive statistics: 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 Scatter diagram of graduation rate and retention rate with retention rate as the independent variable: Figure 1: Scatter diagram of retention rate and graduation rate Multiple regression analysis: 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 FINDINGS 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 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 rates 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). 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. RECOMMENDATIONS 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. REFERENCES Argentiero, P., Morris, R. and Tolson, R. (1969).The X statistic and the goodness of fit test. Washington, D.C.: National Aeronautics and Space Administration. Bekker, P. and Kleibergen, F. (2001).Finite-sample instrumental variables inference using an asymptotically pivotal statistic. Amsterdam: Tinbergen Institute. Boden, G. (2011). Retention and Graduation Rates: Insights from an Extended Longitudinal View. Journal of College Student Retention: Research, Theory and Practice, 13(2), pp.179-203. HaÃÅ'ˆrdle, W. and Simar, L. (2012).Applied multivariate statistical analysis. Berlin: Springer. Heuser, B., Drake, T. and Owens, T. (2012). Evaluating Cross-National Metrics of Tertiary Graduation Rates for OECD Countries: A Case for Increasing Methodological Congruence and Data Comparability. Journal of College Student Retention: Research, Theory and Practice, 14(1), pp.9-35. Heyneman, S. (2012). Introduction: Student Progress toward Graduation: An International Topic of Concern. Journal of College Student Retention: Research, Theory and Practice, 14(1), pp.1-8. Hoyert, M., O'dell, C. and Hendrickson, K. (2012). Using Goal Orientation to Enhance College Retention and Graduation Rates. plat, 11(2), p.171. Kim, G. and Chambers, R. (2011). Regression Analysis under Probabilistic Multi-Linkage.Statistica Neerlandica, 66(1), pp.64-79. Kobayashi, H., Mark, B. and Turin, W. (2012).Probability, random processes, and statistical analysis. Cambridge: Cambridge University Press. Miller, D. (1985).Exponential order statistic models of software reliability growth. [Washington, D.C.]: National Aeronautics and Space Administration, Scientific and Technical Information Branch. Montgomery, D., Peck, E. and Vining, G. (2012).Introduction to linear regression analysis. Hoboken, NJ: Wiley. Pardoe, I. (2012).Applied regression modeling. Hoboken, NJ: Wiley. Sprinthall, R. (2012).Basic statistical analysis. Boston: Pearson Allyn Bacon. XUE, L. (2010). Empirical Likelihood Local Polynomial Regression Analysis of Clustered Data.Scandinavian Journal of Statistics, 37(4), pp.644-663.

Whitman Versus Frost Structure of Modern Poetry Essay Example

Whitman Versus Frost: Structure of Modern Poetry Essay Structure is a major consideration in poetry and also represents an issue that many critics and poets argue about.For some, a poem is not a real poem without some kind of formal structure.To many of these people, a poet writing without structure should not be considered a true poet.For others, structure is viewed as limiting a poem.The question then, is who is right in this argument.Is structure necessary to a poemOr does structure just get in the way of good poetryA consideration of two major poets will show that both unstructured and structured forms are not only acceptable, but capable of resulting in poets that are considered among the best ever.These two poets are Walt Whitman and Robert Frost, each poet on the opposite of the argument and yet both poets using their opposite approach to create effective poetry.This leads to the final answer, which is that the important point is not whether or not structure is used, but whether the poet uses either structure or the absence of str ucture Leaves of Grass was Whitmansfirst published book and was noticed by critics mainly because Whitman rejected standard verse form.In saying that the work was noticed, it is important to emphasize that the work was largely criticized for this aspect of it.One source describes the criticism as being because of its innovation in verse form that it, the use of free verse in long rhythmical lines with a natural, organic structure (The Columbia Electronic Encyclopedia).At the same time, it is important to note that the criticism that occurred should not be seen as a sign of Whitmans failure.Instead, it is best seen as a sign of Whitmans ability to question the methods of the time and attempt something new. The other important point about Whitmans free verse structure is that it was not something created by accident.Instead, Whitman made a considere