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    A cricket coach compared 3 training groups having 10 players in each group by using one way Analysis of variance (ANOVA). Results revealed sum of squa
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    A cricket coach compared 3 training groups having 10 players in each group by using one way Analysis of variance (ANOVA). Results revealed sum of squares between groups (ss)b = 134.6 and sum of squares within groups (ss)w = 110.1. which is the value of F-ratio?

    A.

    15.60

    B.

    16.60

    C.

    16.05

    D.

    16.50

    Correct option is D

    To calculate the F-ratio for a one-way Analysis of Variance (ANOVA), we use the formula:
    F=Mean Square Between Groups (MSb)Mean Square Within Groups (MSw)F = \frac{\text{Mean Square Between Groups (MS}_b\text{)}}{\text{Mean Square Within Groups (MS}_w\text{)}}F=Mean Square Within Groups (MSw​)Mean Square Between Groups (MSb​)​
    Step 1: Determine Degrees of Freedom · dfb=k−1df_b = k - 1dfb​=k−1, where kkk is the number of groups. dfb=3−1=2df_b = 3 - 1 = 2dfb​=3−1=2
    · dfw=N−kdf_w = N - kdfw​=N−k, where NNN is the total number of players, and kkk is the number of groups. dfw=30−3=27df_w = 30 - 3 = 27dfw​=30−3=27
    Step 2: Calculate Mean Squares · Mean Square Between Groups (MS b_bb​):
    MSb=Sum of Squares Between Groups (SSb)dfbMS_b = \frac{\text{Sum of Squares Between Groups (SS}_b\text{)}}{df_b}MSb​=dfb​Sum of Squares Between Groups (SSb​)​ MSb=134.62=67.3MS_b = \frac{134.6}{2} = 67.3MSb​=2134.6​=67.3
    · Mean Square Within Groups (MS w_ww​):
    MSw=Sum of Squares Within Groups (SSw)dfwMS_w = \frac{\text{Sum of Squares Within Groups (SS}_w\text{)}}{df_w}MSw​=dfw​Sum of Squares Within Groups (SSw​)​ MSw=110.127≈4.074MS_w = \frac{110.1}{27} \approx 4.074MSw​=27110.1​≈4.074
    Step 3: Calculate F-Ratio F=MSbMSwF = \frac{MS_b}{MS_w}F=MSw​MSb​​ F=67.34.074≈16.50F = \frac{67.3}{4.074} \approx 16.50F=4.07467.3​≈16.50
    Final Answer: The F-ratio is 16.50.
    Correct Option: (d)
    Additional Information: 1. The F-ratio in ANOVA indicates whether the group means differ significantly. A higher F-value suggests stronger evidence against the null hypothesis.
    2. Critical values of F depend on the degrees of freedom and the significance level (e.g., α=0.05\alpha = 0.05α=0.05).
    3. One-way ANOVA assumes:
    · Independence of observations.
    · Homogeneity of variances.
    · Normally distributed groups.

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