If two regression coefficients are found to be - 0.6 and -1.4, the correlation coefficient will be

• 0.92

• 0.43

• - 0.43

• - 0.92

The iteration formula x_{n + 1} = x_n - $\frac{\mathrm{f}\left({\mathrm{x}}_{\mathrm{n}}\right)}{\mathrm{f}\text{'}\left({\mathrm{x}}_{\mathrm{n}}\right)}$ is commonly known as

• Bisection method

• Newton-Raphson method

• False-positions method

• None of the above

The coefficient of correlation between x and y is 0.8, whereas the regression coefficient of y on x is 0.2, then the
regression coefficient of x on y will be

• - 3.2

• 3.2

• 4

• 0.16

If the variance oftwo variables x and y are respectively 9 and 16 and covariance is 8, then the coefficient of correlation between x and y will be

• $\frac{2}{3}$

• $\frac{8}{3\sqrt{2}}$

• $\frac{9}{8\sqrt{2}}$

• $\frac{2}{9}$

If one line ofregression coefficient is less than unity, then the other will be

• less than unity

• equal to unity

• greater than unity

• All of these

If lines of regression are 3x+ 12y = 19 and 3y+ 9x = 46, then value of r_xy will be

• 0.289

• - 0.289

• 0.209

• None of these

Two lines of regressions are given by x + 2y - 5 = 0 and 2x + ky - 8 = 0. If ${{\mathrm{\sigma }}_{\mathrm{x}}}^2 = 12$ and ${{\mathrm{\sigma }}_{\mathrm{y}}}^2 = 4$, then the value of k is

• 1

• 2

• 3

• 4

If both the coefficients of regression between x and y are 0.8 and 0.2, then the coefficient of correlation between them will be

• 0.4

• 0.6

• 0.3

• 0.5

If the angle between two lines of regression is $\mathrm{\theta }$, then the value of $\mathrm{\theta }$ will be

• ${\tan }^{-1}\left[\frac{{\mathrm{b}}_{\mathrm{yx}} - {\displaystyle \frac{1}{{\mathrm{b}}_{\mathrm{xy}}}}}{1 + {\displaystyle \frac{{\mathrm{b}}_{\mathrm{xy}}}{{\mathrm{b}}_{\mathrm{yx}}}}}\right]$

• ${\tan }^{-1}\left[\frac{{\mathrm{b}}_{\mathrm{yx}} - {\displaystyle {\mathrm{b}}_{\mathrm{xy}} - 1}}{{\mathrm{b}}_{\mathrm{xy}} + {\mathrm{b}}_{\mathrm{yx}}}\right]$

• ${\tan }^{-1}\left[\frac{{\mathrm{b}}_{\mathrm{xy}} - {\displaystyle \frac{1}{{\mathrm{b}}_{\mathrm{yx}}}}}{1 + {\displaystyle \frac{{\mathrm{b}}_{\mathrm{xy}}}{{\mathrm{b}}_{\mathrm{yx}}}}}\right]$

• ${\tan }^{-1}\left[\frac{{\mathrm{b}}_{\mathrm{yx}} - {\displaystyle {\mathrm{b}}_{\mathrm{xy}}}}{1 + {\mathrm{b}}_{\mathrm{xy}} . {\mathrm{b}}_{\mathrm{yx}}}\right]$

If two lines of regression are 3x + 12y = 19 and 9x + 3y = 46, then the value of r_xy will be

• 0.289

• - 0.289

• 0.209

• None of these