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    Testing of hypothesis, Interpreataion of linear correlation

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    1. When using the F-statistic for hypothesis testing of the variance, which sample variance is the numerator and which sample variance is the denominator?

    2. How do you interpret the linear correlation coefficient?

    3. How do you test the equality of population variances?

    4.How do you test the significant differences between treatment means?

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    Solution Preview

    1 When using the f-statistic for hypothesis testing of the variance, which sample variance is the numerator and which sample variance is the denominator?

    Numerator: Variance among the sample means
    Denominator: Within sample variance

    2. How do you interpret the linear correlation coefficient?

    When one variable increases as the other increases the correlation is positive; when one decreases as the other increases it is negative. The complete absence of correlation is represented by 0.

    The primary measure of linear correlation is the Pearson product-moment correlation coefficient (which is symbolized by the lower-case Roman letter r). The value of r ranges in value from r=+1.0 for a perfect positive correlation to r= -1.0 for a perfect ...

    Solution Summary

    The following posting answers four questions on F-statistic for hypothesis testing of the variance, linear correlation, equality of population variances, differences between treatment means.

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