Test the hypothesis that the variances in the regions' profitability (ROA) are equal.
ANOVA helps in predicting the relation between variable groups towards the dependent variable (ROA) based on coherent properties of the independent variable (Region) (Creswell, 2009). Thus, ANOVA statistical measurement method can be performed on each group to find out that variances in the regions' profitability (ROA) are equal or not. Null and alternate hypothesis for the test is given below.
Null hypothesis:
Ho = µ1 = µ2 = µ3
There is no statistically significant difference between average ROA of Asia, Europe, and North American region.
Numeric form: µ (Average ROA of Asian Region) = µ (Average ROA of European Region) = µ (Average ROA of North American Region)
Alternate hypothesis:
H1 = µ1 ? µ2 ? µ3
There is statistically significant difference between average ROA of Asia, Europe, and North American region.
Numeric form: µ (Average ROA of Asian Region) ? µ (Average ROA of European Region) ? µ (Average ROA of North American Region)
Descriptive statistics of the ANOVA are presented in the below table. However, main important column in the data are first and significance column. Main notable thing to note is that sum of squares for the data is higher for the within groups as compare to between groups. Between Groups represent the 1336.92 sum of squares out of 68991.43; whereas, Within Groups constitute 67654.51 sum of square value in total proportion of variance. F-value stood at 9.357, which is significant at 95% confidence interval level (p < 0.05). This shows that ANOVA test for the two selected variables result in rejecting the null hypothesis and accepting the alternate hypothesis, which states that variances in the regions' profitability (ROA) are not equal.
ANOVA
Return on Asset
Sum of Squares
df
Mean Square
F
Sig.
Between Groups
1336.921
2
668.460
9.357
.000
Within Groups
67654.505
947
71.441
Total
68991.426
949
Is there evidence to suggest that the mean profitability of each region is significantly different from the others? Explain.
Above test define that variances in the regions' profitability (ROA) are not equal for all regions. This represents that average profitability of some regions differ significantly from other region's ROA. In order to assess the regions that have unequal variance, post-hoc Tukey test is conducted on the data to determine the unequal relation between regions with respect to the ROA. Table presented below shows the post hoc Tukey test analysis. Significance values highlighted in bold shows that relations do not satisfy the null hypothesis relation.
Therefore, at 0.05 alpha levels, we can conclude that mean profitability (ROA) of Asian and European region is not equal (p=0.0005). Similarly, mean profitability (ROA) is not equal for Asian and North American region at 0.05 alpha levels (p=0.004), resulting in rejecting the null hypothesis (Jackson, 2008).
Multiple Comparisons
Return on Asset
Tukey HSD
(I) Region
(J) Region
Mean Difference (I-J)
Std. Error
Sig.
95% Confidence Interval
Lower Bound
Upper Bound
Asia
Europe
-2.2156568*
.5846574
.000
-3.588081
-.843233
North America
-2.8656486*
.8928480
.004
-4.961518
-.769779
Europe
Asia
2.2156568*
.5846574
.000
.843233
3.588081
North America
-.6499918
.8933058
.747
-2.746936
1.446953
North America
Asia
2.8656486*
.8928480
.004
.769779
4.961518
Europe
.6499918
.8933058
.747
-1.446953
2.746936
*. The mean difference is significant at the 0.05 level.
Question 2: By means of multiple regression analysis, investigate the determinants of profitability (ROA) using SIZE, SHARE, LEV, LIQ and ...