United Nation Work and Life Balance

Work and Life Balance

The eleven (11) respondents of this study believed that “The environment in this organization supports a balance between work and personal life” as evidenced with the mean score of 3.65 and standard deviation of 1.09. There was a big difference between Male and female with respect to this topic, there was 4.00 mean score in male respondents and standard deviation of 0.63 which was classified as Agree while female has 3.22 mean score and standard deviation of 1.39 classified as Undecided.

Analysis of Correlation between male and female work and life balance in United Nation Secretariat

There is no significant correlation between male and female work and life balance in United Nation Secretariat headquarters as evidenced by the computed chi-square value of 8.250 under the degree of freedom 6 and tabulated value of 12.59 with 0.05 level of significant.

Western Bank Financial Statement Analysis

Analysis of the Western Bank Financial Statement
Ernst & Young Auditing
2009 Angelbert D. Morales

I. Introduction
Western Bank is a financial institution with 40,000 account holders and with 15 different branches. Its main location can be found in Southwestern Ontario. It also has 20 different types of deposit account and 20 type of loan.
In order to verify the reasonableness of some of the numbers reported in Western financial statements. The researcher scrutinized the informational data. This is to investigate the lapses of the computed data done by the Western Bank.

The researcher calculated the total interest income by multiplying the interest rate on each type of loan and the loan balance. Then summed over all type of loans and summed over all time periods.

Likewise, the informational data will give the Western Bank manager a broader level of understanding on the computation of the total interest income per month and even per year.

Heart and Lungs Survival ratio

Another finding in my biostatistics project was heart and lungs organ surgery. The issue here is the survival ratio of the patient. It has been found out that there is greater heart operation than lung operation in the study.

Heart Operation survival ratio
There were sixty nine (69) heart organs received, found no complication after surgery or approximately seventy one percent (71.13%) while twenty eight (28) heart organ or twenty eight point eighty seven percent (28.87%) were found to have complications after surgery.

Lungs Operation survival ratio
There were thirty two (32) or seventy eight percent (78%) were found no complication after surgery. However there were 9 lungs organ has a complication after surgery or approximately twenty one point ninety five percent (21.95%).

Overall Implication
This means that two third (2/3)of the heart and lungs organ received after surgery have no complications, however, one third (1/3) had complication. This means that there is ratio of survival was two is to one (2:1).

Conclcusion Large: Equity Valuation using accounting numbers

Large sample

In this paper, the researcher empirically examined also the success of multiple regression model. The researcher investigated if the Assets turnover, Profit margin, Equity Multiplier, and Return on total assets have no effect on the Equity Valuation from the informational data of LUVLE course website: https://luvle.lancs.ac.uk/Acfin/703.nfs. The researcher also used Frequency distribution and analysis of variance (ANOVA).

This paper examined the informational data of LUVLE course website: https://luvle.lancs.ac.uk/Acfin/703.nfs. The researcher discovered that the Assets turnover, Profit margin, Equity Multiplier, and Return on total assets have significant effect on the Return on Equity from the informational data of LUVLE course website.

This means that other variables can affect the result of the equity valuation. The researcher suggested the additional parameters for the greater accuracy of the model.

Conclusion-small: Equity Valuation using accounting numbers

VII. CONCLUSION:
Small sample
In this paper, the researcher empirically examined the success of multiple regression model. The researcher investigated if the R&D to Total Assets, Intangibles to Total Assets, Assets turnover, Profit margin, Equity Multiplier, and Return on total assets have no effect on the Equity Valuation from the informational data of LUVLE course website: https://luvle.lancs.ac.uk/Acfin/703.nfs. The researcher also used Frequency distribution and analysis of variance (ANOVA).
This paper examined the informational data of LUVLE course website: https://luvle.lancs.ac.uk/Acfin/703.nfs. The researcher discovered that the R&D to Total Assets, Intangibles to Total Assets, Assets turnover, Profit margin, Equity Multiplier, and Return on total assets have an effect on the Equity Valuation from the informational data of LUVLE course website. This means that other variables can affect the flaws of the equity valuation. The researcher suggested the additional parameters for the greater accuracy of the model.

Graph 4: Equity Valuation using accounting numbers

The statistical informational data was from LUVLE course website: https://luvle.lancs.ac.uk/Acfin/703.nfs.
It can be gleaned in Graph 4 above, that there were seven Firms who makes a remarkable inflation in terms of ratio analysis. Firm 513 got the highest inflation of Assets turnover, Profit margin and Equity Multiplier which range almost 6000 and followed by Firm 129, range above 5000. Third Firm who got Assets turnover, Profit margin and Equity Multiplier is 671, then 702, 607, 94 and 478.
Summary of the graphs were scrutinized by the researcher. It was found out that only three Firms got the high inflation. These Firms were Firm 702, Firm 671 and Firm 478. This implies that the Firms are performing well in the stock market place and they have good inflation elasticity. It was notable that some companies were also trying their best to be on top such as Firm 513, Firm 129, Firm 607, Firm 624, and Firm 165. This can be seen in their inflation elasticity variables.
The Analysis of Variance was used to determine if the Assets turnover, Profit margin, Equity Multiplier, and Return on total assets have an effect on the Equity Valuation. The null hypothesis is that the Assets turnover, Profit margin, Equity Multiplier, and Return on total assets have no effect on the Equity Valuation.
Thus, all independent variables have no significant effect on the equity valuation: Ho: μ1 = μ2 = μ3= μ4, or Ho. We assume that there should be at most five percent chance of erroneously rejecting a true Ho. Thus we specify a level of significance of 0.05. We used F-distribution and an Analysis of variance (ANOVA)test , and next step is to define the rejection or critical region. The degree of freedom numerator value is 4 and the degree of freedom denominator value is 706. So with α = 0.05, the critical value of F in this analysis of variance test is F0.05 (4,706) = 2.73.
The final statistical decision is rejected the null hypothesis. Since computed F (F c) is greater than Tabulated F (Ft), Ho is rejected and thus, all the independent variables of this study have a significant effect on the equity valuation should be considered as acceptance of the alternative hypothesis. The result of the “Analysis of Variance” (ANOVA) shows that the computed F (21.875) is greater than the tabular values of F-statistics at 0.05 degree of freedom (2.37).
The Regression results are as follows: the unbiased estimator of the variance of the error in the multiple regression model is equal to 2740.285. There is small value of MSE denominator than the MSE numerator (59944.883) so the estimator is a good fit of the regression. Standard error of estimate is equal to 52.34773. Multiple coefficient of determination is .105. (R^2) and an adjusted multiple coefficient of determination is equal to .110 (R2) showed that the data produced a good predictions. This was stated because the adjusted R^2 is closer to the unadjusted R^2.

Large Sample Result: Equity Valuation using accounting numbers

Large sample
This section presents the analysis of the data on the study to find out if the Assets turnover, Profit margin, Equity Multiplier, and Return on total assets have an effect on the Equity Valuation. The Multiple Regression model were used to examined the effect of the other values to the return on equity using LUVLE course website informational data
The descriptive statistics was also used in this study for the presentation purposes. Graphs 3 to 4 show the inflation of the elasticity of the variables.

The statistical informational data was from LUVLE course website: https://luvle/.lancs.ac.uk/Acfin/703.nfs.

From Graph 3, shows that there were 710 selected companies or firm. It is notable that there were 6 firms who got high income before extraordinary items, sales, and assets. Firm 702 got the highest inflation of income before extraordinary items, sales, and assets which range between 400000 to 450000 and followed by Firm 94, range near 40000. Third Firm who got income before extraordinary items, sales, and assets is 671, then 624,165 and 478.

Graph 2:Equity Valuation using accounting numbers

The statistical informational data was from LUVLE course website: https://luvle.lancs.ac.uk/Acfin/703.nfs.
From Graph 2 above, the researcher found out that there were two Firms who makes a remarkable inflation in terms of ratio analysis. The Firm 6 got the highest inflation of RTA, ITTA, Assets turnover, Profit margin and Equity Multiplier which range above 20 and followed by Firm 21, range almost 20. There were three Firms who were almost on range 10. The three Firms were 9, 12, and 24.
Summary of the graphs were scrutinized by the researcher. It was found out that only Firm 6 got high inflation. The Firm 21 got a high Analysis of ratio but slightly lows in terms of R & D. This implies that the only Firm 6 perform well in the stock market place and it has good inflation elasticity. It was notable that some Firms were also trying their best to be on top such as Firm 9, Firm 2, Firm 8, Firm 5, and Firm 4. This can be seen in their inflation elasticity variables.
The Analysis of Variance was used to determine if the R&D to Total Assets, Intangibles to Total Assets, Assets turnover, Profit margin, Equity Multiplier, and Return on total assets have an effect on the Return on Equity. The null hypothesis is that the Assets turnover, Profit margin, Equity Multiplier, R&D to Total Assets, Intangibles to Total Assets, and Return on total assets have no effect on the Equity Valuation.
Thus, Ho: μ1 = μ2 = μ3= μ4= μ5= μ6, or Ho: All independent variables have no significant effect on the equity valuation. The alternative is that not all independent variables have a significant effect on the return on equity. Let’s assume that there should be at most five percent chance of erroneously rejecting a true Ho. Thus we specify a level of significance of 0.05. We used F-distribution and an Analysis of variance (ANOVA)test , and next step is to define the rejection or critical region. The dfnum value is k-1, or 6 and the dfden value is T-k, or 18. So with α = 0.05, the critical value of F in this analysis of variance test is F0.05 (6,18) = 2.66. The decision Rule is Reject Ho in favor of Ha if the value of the computed F is greater than the value of tabulated F. Otherwise, do not reject Ho. The next step is to compute the test statistic. Find the computed F, by dividing the mean sum of square of regression value by the mean sum of square of residual value. The final step now is to make the statistical decision. Since computed F (F c) is greater than Tabulated F (Ft), Ho is rejected and thus, not all the independent variables of this study have a significant effect on the return on equity. The result of the “Analysis of Variance” (ANOVA) shows that the computed F (13.656) is greater than the tabular values of F-statistics at 0.05 degree of freedom (2.66). Hence, Ho must be rejected.
The Regression results are as follows: the unbiased estimator of the variance of the error in the multiple regression model is equal to .010. There is small value of MSE denominator than the MSE numerator (.131) so the estimator is a good fit of the regression. Standard error of estimate is equal to .09777. Multiple coefficient of determination is .820 (R2) and an adjusted multiple coefficient of determination is equal to .760 (R2) showed that the data produced a good predictions. This was stated because the adjusted R^2 is closer to the unadjusted R^2.

Results: Equity Valuation using accounting numbers

VI. RESULTS
Small sample
This section presents the analysis of the data on the study to find out if the R&D to Total Assets, Intangibles to Total Assets, Assets turnover, Profit margin, Equity Multiplier, and Return on total assets have an effect on the Equity Valuation. The Multiple Regression model was used to examine the effect of the other values to the equity valuation using LUVLE course website informational data. The descriptive statistics was also used in this study for the presentation purposes. Graphs 1 to 2 show the inflation of the elasticity of the variables.

The statistical informational data was from LUVLE course website: https://luve.lancs.ac.uk/Acfin/703.nfs.
Graph 1 above shows that out of 25, only 6 companies have a high R & D Range. The Firm number 6 got the highest inflation of R & D value which range between 150,000,000 and followed by Firm 5 and Firm 2, range near 50,000,000. The fourth firm who got R & D lower than 50,000,000was Firm 4. This implies that there were only few Firms who focused on the R & D. This means that many Firms were afraid to gamble or to take the risk in spending too much in Research and Development (R & D). This also shows that even though Firms belong to above £ 10,000 R & D, there were still other factors that can affect the interest of the investors.

Equity Valuation using accounting numbers

CHAPTER-3: METHODOLOGY
3-1 Research Methodology

The main objective of this chapter is to identify how the chosen research methodologies that will match the main objective of the dissertation question and how it will be achieved. Given the two types of research methodology between qualitative and quantitative research, this paper has to make a choice of one over the other or a combination of both. This paper admits that the quantitative research is carried out through obtaining primary data such as questionnaire, while qualitative research is a research that may make use of qualitative information through interviews and observations. Given the fact that the purpose of this research is to test the relationship of accounting numbers with the equity valuation, quantitative research is more of the required type for this kind of work. This does not however exclude the use of qualitative research as could be observed in content analysis from statements of various authors. Therefore, a quantitative approach is used here that it will enable the researcher to make use of the numerical and to explore the details of individual perceptions over phenomena. As complement to quantitative research this paper will also use qualitative methods particularly in expounding on the merits of one model over the other for it is in this context that qualitative approach assumes undeniable significance. This paper therefore first uses the quantitative approach by using both the small sample size and large sample size analysis to confirm or the deny the thesis of this dissertation the accounting numbers are good and reliable predictor for stock valuation and to under stand the finer points of the research qualitative research will be used.
Under the large sample size, the researcher used about more than 180 registered companies in UK by extracting relevant accounting numbers such as net income , total assets, etc in relation to total equity valuation of the firms . This paper has chosen multiple regressions to test of degree of relationships for the dependent variable to the independent variables
Under the small sample size approach, the researcher tried to reduce the large sample size from 180 to 50 until it reached 25. The basis for bringing the l80 sample size to 50 is to get only those that have R&D values of £10,000 or more. To get to 25, only those whose balance sheet date was December, 2004 were considered.
The paper will compare the results of analysis between the large and small sample size on whether there is basis to confirm the validity of finding. As a rule if the result of the first is confirmed by the second, then such would be a good sign of the characteristics of the models using accounting numbers.
Before the discussion of the application of the small size sample and large sample size, further discussion of the methodology will also be further discuss to enlighten the reader of this paper.