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CHAPTER 4

FINDING AND ANALYSIS

4.1 INTRODUCTION

This chapter presents the finding and data analysis for the study. The data has been analyzes using statistical package for social science (SPSS) software. The first part in this chapter will briefly explained on the data and its simple statistical result. The second part of this chapter want to examined the data to test how the independent variables that have been chosen to fit the model using R-square (R2). Next this chapter will examine the possible relationship between each independent variables using coefficient relationship with its dependent variables. Further in this chapter will discover the level of significant relationship between each independent variable using the T-statistics. Later, the result will be obtained on the combination of independent variables which can be used as predictors to the dependent variables using the F-statistics. The analysis on each part will help to answer the research questions asked by the researcher as well as answer the hypothesis in this study.

4.2 DESCRIPTIVE STATISTICS

A descriptive statistics is a brief description which tries to summarize a given data set. The data set are measures of central tendency for example mean, maximum and minimum value. Descriptive statistics provide a useful summary to the researcher to the given amount of data used in the research study.

4.2.1 BOSNIA HERZEGOVINA

Descriptive Statistics

N Minimum Maximum Mean Std. Deviation

ROA 25 -4.3700 8.4400 .616800 1.9654637

ROE 25 -41.9200 17.3000 3.904800E0 11.5150330

GDP 25 -.0588 .2426 .122388 .1104654

INF 25 -.4000 7.4000 3.640000E0 2.9258902

PS 25 25.9434 30.2885 2.775723E1 1.6981657

Valid N (listwise) 25

Table 4.1: Descriptive Statistics of BIH

The result generated from the sample size of the country BIH show that there is total of 25 data has been used for the research study. All variables were tapping on positive scale as can be seen in column number four with the highest value is represent by the variable PS (30.2885) and the lowest value is GDP (0.2426). The dependent variable, ROE show the highest value in mean at 3.904800E0 mean while GDP show the lowest value at 0.122388. The standard deviation of ROE is the highest (11.5150330) as to compare with the lowest value present by GDP (0.1104654).

4.2.2 MALAYSIA

Descriptive Statistics

N Minimum Maximum Mean Std. Deviation

ROA 25 .2400 1.6400 .975200 .3992610

ROE 25 3.1300 27.3500 1.386720E1 6.1843455

GDP 25 -.1295 .1924 .098377 .1210521

INF 25 .6000 5.4000 2.920000E0 1.6360522

PS 25 46.6981 61.0577 5.342501E1 4.8356570

Valid N (listwise) 25

Table 4.2: Descriptive Statistics of MYS

The result generated from the sample size of the country MYS show that there is total of 25 data has been used for the research study. All variables were tapping on positive scale as can be seen in column number four with the highest value is represent by the variable PS (61.0577) and the lowest value is GDP (0.1924). The independent variable, PS show the highest value in mean at 5.342501E1 mean while GDP show the lowest value at 0.098377 The standard deviation of ROE is the highest (6.1843455) as to compare with the lowest value present by GDP (0.1210521).

4.3 COEFFICIENT OF DETERMINATION (R-SQUARE)

Coefficient of determination (R2) is used to measure the correlation between dependent and independent variable in the regression analysis. It helps the researcher to measure how well the overall equation can explain the dependent variables. The value is range from 0 to 1. The higher values indicate that the dependent variable can be explained by the particular independent variable.

Coefficient of Determination

COUNTRY DV R R2

BIH ROA 0.166 0.027

ROE 0.426 0.181

MYS ROA 0.165 0.027

ROE 0.222 0.049

Table 4.3: Coefficient of Determination of BIH and MYS

Table 4.3 represents the result regressed from SPSS that convey the value of coefficient of determination, R-square for both countries tested which are BIH and MYS. The values of R for the dependent variable ROA for the country BIH show a weak relationship between dependent variable and its independent variables since its lower than average of 0.5. However, it shows that the value of R for the dependent variable ROE show much positive relationship between the dependent variable ROE with its independent variable GDP, inflation and political stability. It explains that only 2.7% of the change of ROA for B...

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