Academia.eduAcademia.edu

Figure 3 – uploaded by emmanuel emeka

See full PDFdownloadDownload figure
Table 3: Raw Data of Guinness Nigeria Plc Source: Financial Statement of Guinness Nigeria Plc Field work 2019 Table 2: Derivatives of the Raw Data for Nigeria Breweries Pic Source: Computation of Financial Statement of Nigerian Breweries Pic Field Work 2019

Table 3 Raw Data of Guinness Nigeria Plc Source: Financial Statement of Guinness Nigeria Plc Field work 2019 Table 2: Derivatives of the Raw Data for Nigeria Breweries Pic Source: Computation of Financial Statement of Nigerian Breweries Pic Field Work 2019

Related Figures (17)

Table 1: Raw Data of Nigerian Breweries Plc Source: Financial Statement of Nigerian Breweries Plc
Table 1: Raw Data of Nigerian Breweries Plc Source: Financial Statement of Nigerian Breweries Plc
Table 5: Raw Data of Nestle Nigeria Plc Source: Financial Statement of Nestle Nigeria Plc Table 4: Derivatives of the Raw Data for Guinness Nigeria Plc Source: Computation of Financial Statement Of Guinness Nigeria Plc Field Work 2019
Table 5: Raw Data of Nestle Nigeria Plc Source: Financial Statement of Nestle Nigeria Plc Table 4: Derivatives of the Raw Data for Guinness Nigeria Plc Source: Computation of Financial Statement Of Guinness Nigeria Plc Field Work 2019
4.1. Normality Test
4.1. Normality Test
The study conducted the descriptive statistics of the relevant variables involved. Table 4.2 illustrates vividly these statistics. It shows total number of observations, mean, median, maximum, minimum, standard deviation, skewness, kurtosis and arque-Bera. The dependent variable which is return on asset ratio shows a minimum value of 0.129170 and a maximum value of 5.305932. The mean value of the dependent variable is 0.755356 and the standard deviation is 1.602153. This implies that there was high fluctuation in return on asset ratio for the years. It can be observed from Table 4.2 that all the variables have positive average values (means). It can be observed also that all the variables show signs of positive skewness while all the variables except account payable ratio have high kurtosis, therefore they are leptokurtic. The study conducted the descriptive statistics of the relevant variables involved. Table 4.2 illustrates vividly thes statistics. It shows total number of observations, mean, median, maximum, minimum, standard deviation, skewness kurtosis and arque-Bera. The dependent variable which is return on asset ratio shows a minimum value of 0.242115 an a maximum value of 3.225994. The mean value of the dependent variable is 1.961074 and the standard deviation i 0.975762. This implies that there was high fluctuation in return on asset ratio for the years. It can be observed from Tabl 4.2 that all the variables have positive average values (means). It can be observed also that only return on asset rati: shows a sign of negative skewness while other variables showed sign of positive skewedness. All the variables excep account payable ratio have high kurtosis.
The study conducted the descriptive statistics of the relevant variables involved. Table 4.2 illustrates vividly these statistics. It shows total number of observations, mean, median, maximum, minimum, standard deviation, skewness, kurtosis and arque-Bera. The dependent variable which is return on asset ratio shows a minimum value of 0.129170 and a maximum value of 5.305932. The mean value of the dependent variable is 0.755356 and the standard deviation is 1.602153. This implies that there was high fluctuation in return on asset ratio for the years. It can be observed from Table 4.2 that all the variables have positive average values (means). It can be observed also that all the variables show signs of positive skewness while all the variables except account payable ratio have high kurtosis, therefore they are leptokurtic. The study conducted the descriptive statistics of the relevant variables involved. Table 4.2 illustrates vividly thes statistics. It shows total number of observations, mean, median, maximum, minimum, standard deviation, skewness kurtosis and arque-Bera. The dependent variable which is return on asset ratio shows a minimum value of 0.242115 an a maximum value of 3.225994. The mean value of the dependent variable is 1.961074 and the standard deviation i 0.975762. This implies that there was high fluctuation in return on asset ratio for the years. It can be observed from Tabl 4.2 that all the variables have positive average values (means). It can be observed also that only return on asset rati: shows a sign of negative skewness while other variables showed sign of positive skewedness. All the variables excep account payable ratio have high kurtosis.
The study conducted the descriptive statistics of the relevant variables involved. Table 4.2 illustrates vividly these statistics. It shows total number of observations, mean, median, maximum, minimum, standard deviation, skewness, kurtosis and arque-Bera. The dependent variable which is return on asset ratio shows a minimum value of 0.240945 and a maximum value of 0.538042. The mean value of the dependent variable is 1.961074 and the standard deviation is 0.975762. This implies that there was high fluctuation in return on asset ratio for the years. It can be observed from Table 4.2 that all the variables have positive average values (means). It can be observed also that only return on asset ratio shows a sign of negative skewness while other variables showed sign of positive skewedness. All the variables except account payable ratio have high kurtosis.
The study conducted the descriptive statistics of the relevant variables involved. Table 4.2 illustrates vividly these statistics. It shows total number of observations, mean, median, maximum, minimum, standard deviation, skewness, kurtosis and arque-Bera. The dependent variable which is return on asset ratio shows a minimum value of 0.240945 and a maximum value of 0.538042. The mean value of the dependent variable is 1.961074 and the standard deviation is 0.975762. This implies that there was high fluctuation in return on asset ratio for the years. It can be observed from Table 4.2 that all the variables have positive average values (means). It can be observed also that only return on asset ratio shows a sign of negative skewness while other variables showed sign of positive skewedness. All the variables except account payable ratio have high kurtosis.
Table 10 showed that return on asset ratio and debt ratio became stationary at first difference while account ceivable ratio and account payable ratio became stationary at second difference. Table 11 showed that return on asset ratio became stationary at second difference while debt ratio, account receivable ratio and account payable ratio became stationary at first difference.
Table 10 showed that return on asset ratio and debt ratio became stationary at first difference while account ceivable ratio and account payable ratio became stationary at second difference. Table 11 showed that return on asset ratio became stationary at second difference while debt ratio, account receivable ratio and account payable ratio became stationary at first difference.
Table 12 showed that return on asset ratio became stationary at first difference while debt ratio, account eceivable ratio and account payable ratio became stationary at second difference.
Table 12 showed that return on asset ratio became stationary at first difference while debt ratio, account eceivable ratio and account payable ratio became stationary at second difference.
Table 4:4.1 shows that the R2 which is 0.327810 is about 32%, therefore it does not have a poor goodness of The F-statistic which is 0.975349 is less than 2.5 while its probability value is more than 5%, it is therefore concluded t it is statistically insignificant. The Durbin-Watson statistic is approximately 2, therefore there is no autocorrelation in model implying it can be used to make a meaningful analysis.
Table 4:4.1 shows that the R2 which is 0.327810 is about 32%, therefore it does not have a poor goodness of The F-statistic which is 0.975349 is less than 2.5 while its probability value is more than 5%, it is therefore concluded t it is statistically insignificant. The Durbin-Watson statistic is approximately 2, therefore there is no autocorrelation in model implying it can be used to make a meaningful analysis.
Table 4:4.2 shows that the R? which is 0.651562 is about 65%, therefore it has a goodness of fit. The F-statistic which is 3.739899 is greater than 2.5 while its probability value being 0.079453 is less than 5%, it is therefore concluded that it is statistically significant. The Durbin-Watson statistic is not approximately 2, therefore there is autocorrelation in the model.
Table 4:4.2 shows that the R? which is 0.651562 is about 65%, therefore it has a goodness of fit. The F-statistic which is 3.739899 is greater than 2.5 while its probability value being 0.079453 is less than 5%, it is therefore concluded that it is statistically significant. The Durbin-Watson statistic is not approximately 2, therefore there is autocorrelation in the model.
Table 4:10 shows that the R? which is 0.547578 is about 55%, therefore it has goodness of fit. The F-statistic which is 2.420653 is less than 2.5 while its probability value being 0.164309 is more than 5%, it is therefore concluded that it is statistically insignificant. The Durbin-Watson statistic is not approximately 2, therefore there is autocorrelation in the model.
Table 4:10 shows that the R? which is 0.547578 is about 55%, therefore it has goodness of fit. The F-statistic which is 2.420653 is less than 2.5 while its probability value being 0.164309 is more than 5%, it is therefore concluded that it is statistically insignificant. The Durbin-Watson statistic is not approximately 2, therefore there is autocorrelation in the model.
4.4.3.3. Step Three Ordinary Least Square is used in testing for the hypothesis. Decision Rule: Reject the null hypothesis if the t — statistics is greater than 2.5 and the probability valueis less than 5%.
4.4.3.3. Step Three Ordinary Least Square is used in testing for the hypothesis. Decision Rule: Reject the null hypothesis if the t — statistics is greater than 2.5 and the probability valueis less than 5%.
Related topics:
BusinessInnovative Development
580 California St., Suite 400
San Francisco, CA, 94104
© 2025 Academia. All rights reserved