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

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

• = A
• < B
• > C
• ≠ D

A relationship where the flow of the data points is best represented by a curve is called_______.

• Linear positive A
• Linear negative B
• Linear relationship C
• Nonlinear relatiobship 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 estimates of the parameters=α and=β are

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

The estimated regression line always passes through

• origin A
• 
  B
• x-axis C
• y-axis D

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

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

• 
  A
• b_yx B
• b_xy C
• S_p D

Regression line x on y is

• 
  A
• 
  B
• 
  C
• 
  D

When b_xy is positive, then b_yx will be _______.

• Negative A
• Positive B
• Zero C
• One 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

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

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 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

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

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

The variable that forms the basis of estimation is called

• regression A
• regressand B
• regressor C
• correlation D