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Value shares and Growth Shares in the UK market (FTSE 350)
Finance & Accounting
Pages 2 (502 words)
ANOVA is a statistical procedure for determining whether the means of several different populations are equal or not. One way ANOVA is a method to analyse the difference between two populations on the basis of one variable.
This means that the significance level of the test is 0.05 or 5%. The null hypotheses are usually accepted when the test is significant statistically at chosen significance level of 5%. When Null hypothesis is rejected it implies that all sample means are not equal. If this is true, it may not be sufficient to give required inference. In such case it might be required to know which sample means differ. To find that out proper confidence interval has to be chosen using small sample procedures based on t-distribution. A parametric correlation test of coefficient and non parametric run test was further used to test the auto correlation for the stock returns over time. When the null hypothesis will be accepted at 5% or 10% level then it can be said that the regression model developed earlier was statistically significant. The marginal significance in the regression model is given by the p-value. When the probability for observing the t-values is large, then the null hypothesis will be true. The value of p ranges from 0 to 1 and it gives the researcher the cut-off level or the lowest significance level below which the null hypothesis may be rejected. If the p-values are very small then the significance of null hypothesis is reduced. Smaller p-values indicate that null hypothesis is not significant and hence should be rejected. ...
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