2nd Year Statistics Chapter 14 Online MCQ Test for 12th Class Statistics Chapter 14 (Simple Linear Regression and Correlation)

The variable, whose resulting value depends upon the selected value of the independent variable is called______.

• Regression A
• Regressor B
• Regressand C
• Coefficient D

r is the ------------ of two regression co-efficient b_yx and b_xy

• arithmetic mean A
• geometric mean B
• harmonic mean C
• median D

A data points falling along a straight line is called______.

• Linear relationship A
• Non-linear relationship B
• Linear positive C
• Scatter diagram D

If the value of any regression coefficient is zero, then two variable are _______.

• Qualitative A
• Correlation B
• Dependent C
• Independent D

The _______ regression line always passes through (X̅, y̅).

• Opposite A
• Estimated B
• Estimates C
• Random D

A set of points in a rectangular coordinate system, where each point represents an observed pair of values is called

• least square regression A
• scatter diagram B
• pie graph C
• regression coefficient D

The straight line graph of the linear equation Y = a + bX, the slope will be upward it_______.

• b = 0 A
• b < 0 B
• b > 0 C
• b ≠ 0 D

A process by which we estimate the value of dependent variable on the basis of one or more independent variable is called_________.

• Residual A
• Correlation B
• Regression C
• Slope D

The value of the coefficient of correlation relies between__________.

• -1 and +1 A
• 0 and 1 B
• -1 and 0 C
• -0.5 and + 0.5 D

The estimates of the parameters=α and=β are

• μ and=σ2 A
• a and b B
• μ andπ C
• χ2 and Z D

• y-intercept A
• x-intercept B
• slope C
• none of these D

Regression line x on y is

• 
  A
• 
  B
• 
  C
• 
  D

If constants are added to or subtracted from the values of the variables, the value of r 

• is negative A
• is positive B
• is zero C
• remains unchanged D

r_xy -------------- r_yx

• = A
• < B
• > C
• ≠ D

The measures of strength of closeness of linear relationship between two variables is called

• simple linear regression A
• composite linear regression B
• simple linear correlation C
• composite linear correlation D

If X and Y are independent, then Cov(x,y) = 0 which implies that

• b_yx = 0 A
• b_xy = 0 B
• ρ = 0 C
• a = 0 D

When b_xy is positive, then b_yx will be _______.

• Negative A
• Positive B
• Zero C
• One D