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

The variable that forms the basis of estimation is called

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

The relationship that describes the dependence of the expected value of the dependent random variable for a given value of the independent non-random variable is called

• equation A
• relation B
• ratio C
• regression D

Regression line x on y is

• 
  A
• 
  B
• 
  C
• 
  D

If r = -1, then there is

• negative correlation A
• perfect negative correlation B
• no correlation C
• average correlation D

The regression equation always passes throught_________.

• (X, Y) A
• (X, y̅) B
• (X̅, Y) C
• (X̅, y̅) D

• S_xy A
• S_yx B
• b_xy C
• b_yx D

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

• Qualitative A
• Correlation B
• Dependent C
• Independent 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 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

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

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

• Regression A
• Regressor B
• Regressand C
• 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
• b_yx B
• b_xy C
• S_p D

The variable, that forms the basis of estimation, is called_______.

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

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