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# Information Technology Project - Essay Example

Summary
Data was collected on Zad Holding Company, a listed company on the Qatar Exchange, and excel used to conduct correlation and regression analysis on relationships between the company’s return on investment, P/E ratio, and P/B ratio.
The results show a weak but positive…

## Extract of sample "Information Technology Project"

Information technology project May 27, Information technology project Data was collected on Zad Holding Company, a listed company on the Qatar Exchange, and excel used to conduct correlation and regression analysis on relationships between the company’s return on investment, P/E ratio, and P/B ratio.
Correlation analysis
The following table shows the correlation analysis results.
Table 1: Correlation analysis results
Correlation analysis

ROE
P/E
P/B
ROE
1

P/E
0.076467
1

P/B
0.308359
0.399738
1
The results show a weak but positive correlation between return on equity and price-earnings ratio (0.076), and this suggests a weak positive relationship between the variables. A strong positive relationship, however, is suggested between return on equity and price-book-ratio (0.074). A strong positive correlation also exists between price-earnings ratio and price-to-book ratio (0.39).
Regression analysis
Regression analysis identifies exact effects and significance of a variable on another (Black, 2011). Table 2 shows regression analysis summary output for the relationship between return on equity and both price-earnings ratio and price-to-book ratio.
Table 2: Summary output
Regression Statistics
Multiple R
0.090123432
R Square
0.008122233
-0.108569269
Standard Error
0.184313633
Observations
20
The developed model is not suitable for explaining a relationship between the variables because of the negative R2 value. This means that additional independent variable is necessary into the model.
The regression model is, further, not significant and cannot be used to explain the relationship.
Figure 3: ANOVA table
ANOVA

df
SS
MS
F
Significance F
Regression
2
0.0047291
0.002364564
0.069604
0.93302724
Residual
17
0.5775158
0.033971515
Total
19
0.5822449

The model is not significant (p=0.933> 0.05, F= 0.069). No significant relationship, therefore, exists between ROE and both P/E and P/B.
The following is the table of coefficients for the relationship.
Table 4: Table of coefficients

Coefficients
Standard Error
t Stat
P-value
Intercept
0.197584
0.237413
0.832238
0.416813
P/E
-0.00644
0.029059
-0.22159
0.82727
P/B
0.266305
0.202444
1.315448
0.205826
Each of the independent variables is not significant (p= 0.827, p= 0.206, > 0.05). The results conclude that no significant relationship exist between ROE and both P/E and P/B.
References
Black, K. (2011). Business statistics: For contemporary decision making. Hoboken, NJ: John Wiley & Sons. Read More
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