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The 2 β coefficient in the formula 2 shows that in the case of a change with a<br />

pound/centime of comprehensive income per share, the price per share changes by<br />

5.37 pounds/centimes.<br />

Table 2. Summary output for simple regression between price per share and basic<br />

earning per share<br />

Regression Statistics<br />

Multiple R 0,472184425<br />

R Square<br />

Adjusted R<br />

0,222958131<br />

Square<br />

Standard<br />

0,210007433<br />

Error 1256,336024<br />

Observations 62<br />

ANOVA<br />

df SS MS F Significance F<br />

Regression 1 27173261,72 27173262 17,215916 0,00010679<br />

Residual 60 94702812,33 1578380<br />

Total 61 121876074<br />

Coefficients<br />

Standard<br />

Error t Stat P-value<br />

~ 979 ~<br />

Lower<br />

95%<br />

Upper<br />

95%<br />

Lower<br />

95,0%<br />

Upper<br />

95,0%<br />

Intercept 729,4754 185,9590 3,922776 0,0002278 357,5021 1101,4488 357,5021 1101,4488<br />

X Variable 1 5,3719 1,2946 4,149207 0,0001068 2,7821 7,9616 2,7821 7,9616<br />

Since Multiple R has a positive value close to 0.5, this shows that between<br />

comprehensive income and price per share there is a direct correlation of medium<br />

intensity. R Square shows us that only 22.29% of the variation of the price per share is<br />

explained by the comprehensive income. Since Significance F has a low value,below<br />

the threshold limit of 0.05, and F is a high value (17.21), we can accept the simple<br />

regression model presented in Formula 2 and validated by Figure 3.

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