(1%) b. The variance is the square of the standard deviation, however, the funda
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(1%) b. The variance is the square of the standard deviation, however, the fundamental difference between the two parameters is: ) The variance is only associated with relationships between two varlables and the standard deviation is not G) The varlance deviation calculates the standard error of the coefficient of correlation in regression analysis H) The variance is directly related to the median of data while the standard deviation is directly related to the mean of data ) None of the above can be used to determine the extent of error in ANOVA analysis while the standard (3%) c. Consider the following case: o-0.01, n-16, s. 9.5, and the hypothesis is H./ 2 10, Hie 10. The test statistic and the critical statistic in this case are (a) 14.25 & 5.23, respectively (b) 11.25&4.23, respectively (c) 12.25&5.23, respectively () None of the above (4%) d. Determine if this statement is correct or false: In a one-factor ANOVA, the objective is to evaluate whether the ratio between the between-treatment variation (MS-Between)) and the Residual variation (MS Residual) is significantly higher the critical F-value so that we can reject that all levels of a factor are equal. Correct (...) False. (...) (1%) e. In a simple regression analysis (one independent variable), the model degree of freedom is 0- 1-. 2 , undefined() (4%) f. In multiple regression analysis, the addition of any variable to the regression model will always result in: (a) increasing R (...,(b) decreasing R (.., c) doubling R (.., or (d) No change in R (. (1%) g, when two independent samples are compared for proportion, the significance of the difference is determined by the following test statistic: = (81-32)-(11-12) pi -P2 D) z0- Pa-P)P(1-P) 71 n2Explanation / Answer
b. Variance and std. dev. - Option G
c.
Test statitics, chi-square = (N-1)(s/sigma)^2 = (16 - 1)*(9.5/10) = 14.25
critical value = 5.2293
Option A is correct
d. This statement is true
e. DF = 1
g. option (D)
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