Regression Survey Model
CHAPTER FOUR
EMPIRICAL RESULTS
4.0 Introduction This chapter discusses about the findings of data and interpretation of the result for this study. The empirical results obtained by running several test by using E-views version 8 and Stata Data Analysis computer software. Test which have been employed in this study are the descriptive statistics, Pooled OLS Model, Breusch-Pagan Lagrange Multiplier (LM) Test, Serial Correlation Test and Multicollinearity Test.
4.1 Descriptive Statistics
Table 3: Description Statistics Result
Dependent Variable: SGR SGR CAPSTR LCAP LIQUIDITY EIARD
Mean 0.6114722 51.35774 9.305538 2.991083 0.6666667
Maximum 62 4501.4 15.05093 59.88 1
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Figure in the parentheses are t-statistics.
2. ** and *** indicate 5% and 1% of significant levels respectively.
According to Pearson Correlation Test results, the null hypothesis and alternative hypothesis as shown below:
H10: There is no significant correlation between capital expenditure and sales growth rate.
H11: There is significant correlation between capital expenditure and sales growth rate.
The results show that the P-value = 0.0000 < 0.05, so, reject the null hypothesis, H10, at confidence level of 0.05, which indicates that there is significant correlation between capital expenditure and sales growth rate. This also proves that there is a negative significant correlation between capital expenditure and sales growth. Negative correlation specifies that when an increase in capital expenditure will cause decrease in sales growth rate and vice versa.
H20: There is no significant correlation between capital structure and sales growth rate.
H21: There is significant correlation between capital structure and sales growth rate.
The results show that the P-value = 0.2874 > 0.05, hence, do not reject the null hypothesis, H20, at 1% of significant level, which indicates that there is no significant correlation between capital structure and sales growth
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