ISBN: - 978-93-88936-09-5 AB y t* − ) Y t * = 2 t − 1.20(B) ANOVA ANOVA test is used to find the significant differences existing among the three or ( t) n 2 more sample groups in relation to a variable. The total variance in a set of data is divided into variation within groups and variation between groups. The ANOVA technique is based on the concept of sum of squared deviations from a mean. Corresponding to the total variance and its two components, we have the total sum of squares (SS), between groups sum of squares (SSb), within groups of squares (SSw) is obtained by combining the sum squares i.e., the squared deviations of every raw score from its sample mean. The formula used is SSw = ∑d2 + ∑d2 + ∑d2 + ∑d2 + ∑d2 + …………………∑d2 1 2 3 4 5 n Where d = a deviation of every raw score of a category from its sample mean. Between groups sum of squares (SSb)is by calculating the difference between each sample mean and the total mean. The squared difference is multiplied by the sample size in the concerned category and these quantities. The formula is SSb= ∑[(x-x1)2 ×n] Where, X = any sample mean X1= the total mean n = the number of scores in any sample SSb = the between groups sum of squares The total sum of squares (SS1) is equal to a sum of within and between groups sum of squares. SS1 = SSb+ SSw 1.20(C) Mean Square The value of the sum of squares tends to become larger as variation increases and also as sample size increases. The mean square (or variance) is obtained by dividing SSb or SSw by the appropriate degrees of freedom. 29 ( *)( n
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