Advanced Statistics in Education M.Ed. 425 (D)

The formula for calculation of  $r_{12.3}$   is

•  $\frac{r_{12\ }-r_{13\ \ }r_{23}}{\sqrt{1-r_{13}^2}\sqrt{1-r_{23}^2}}$  

•  $\frac{r_{13\ }-r_{12\ \ }r_{23}}{\sqrt{1-r_{12}^2}\sqrt{1-r_{23}^2}}$  

•  $\frac{r_{23\ }-r_{12\ \ }r_{13}}{\sqrt{1-r_{12}^2}\sqrt{1-r_{13}^2}}$  

•  $\frac{r_{14\ }-r_{23\ \ }r_{13}}{\sqrt{1-r_{23}^2}\sqrt{1-r_{13}^2}}$  

The formula for calculation of Biserial Correlation is

• $\frac{M_{p\ }-M_t}{M_q}\times\sqrt{pq}$

• $\frac{M_{p\ }-M_q}{\sigma_t}\times\sqrt{\frac{p}{q}}$

• $\frac{M_{p\ }-M_q}{\sigma_t}\times\frac{pq}{y}$

• $\frac{M_{t\ }-M_q}{\sigma_t}\times\frac{pq}{y}$

The formula for calculating Point Biserial Correlation is

• $\frac{M_{p\ }-M_q}{\sigma_t}\times\frac{p}{q}$

• $\frac{M_{p\ }-M_q}{\sigma_t}\times\sqrt{pq}$

• $\frac{M_{p\ }-M_q}{\sigma_t}\times\sqrt{\frac{p}{q}}$

• $\frac{M_{p\ }-M_q}{\sigma_t}\times pq$

Phi Coefficient is calculated by the formula

• $\frac{BC-AD}{\sqrt{\left(A+D\right)\left(B+C\right)\left(C+D\right)\left(A+C\right)}}$

• $\frac{AD-BC}{\sqrt{\left(A+B\right)\left(B+D\right)\left(C+D\right)\left(A+C\right)}}$

• $\frac{AD-BC}{\sqrt{\left(A+D\right)\left(B-C\right)\left(C+D\right)\left(A+C\right)}}$

• $\frac{AD+BC}{\sqrt{\left(A-B\right)\left(B-D\right)\left(C-D\right)\left(A-C\right)}}$

The regression equation for predication of Y is

• $Y-M_x=r\ \frac{\sigma_x}{\sigma_y}\ \left(X-M_{y\ }\right)$

• $X-M_x=r\ \frac{\sigma_x}{\sigma_y}\ \left(Y-M_{y\ }\right)$

• $Y-M_y=r\ \frac{\sigma_y}{\sigma_x}\ \left(X-M_{x\ }\right)$

• $Y-M_y=r\ \frac{\sigma_x}{\sigma_y}\ \left(X-M_{x\ }\right)$

The regression equation for predication of X is

• $X-M_x=r\ \frac{\sigma_y}{\sigma_x}\ \left(Y-M_{y\ }\right)$

• $Y-M_x=r\ \frac{\sigma_x}{\sigma_y}\ \left(X-M_{y\ }\right)$

• $X-M_y=r\ \frac{\sigma_x}{\sigma_y}\ \left(Y-M_{x\ }\right)$

• $X-M_x=r\ \frac{\sigma_x}{\sigma_y}\ \left(Y-M_{y\ }\right)$

The formula for calculating the total sum of squares in Two-Way ANOVA is

• $\Sigma X^2+C$

• $\frac{\Sigma X^{2\ }}{C}$

• $\Sigma X^2-C$

• $\Sigma X^2+\Sigma C^2$

Which is an assumption underlying the Analysis of Variance

• Additivity of Effects

• Normal Distribution

• Homogeneity of Variance

• All the above

Biserial Coefficient of Correlation is used when the dichotomy is

• Natural

• Linear

• Artificial

• Corelational

Phi Coefficient is used when

• One Variable is Continuous and the Other has Artificial Dichotomy

• One Variable is Continuous and the Other has Natural Dichotomy

• Both Variables are Continuous and have Artificial Dichotomy

• Both Variables are Continuous and have Natural Dichotomy