ICS Part 2 Statistics Chapter 14 Online Test

If b_yx = 0.89 and b_xy = 0.75, then r=

• 0.89 A
• 0.28 B
• 0.98 C
• 0.82 D

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

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

• 37 A
• 132 B
• 32 C
• cannot be calculated 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

• 
  A
• b_yx B
• b_xy C
• S_p 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 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

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

In simple linear regression, the number of unknown constants are:

• Two A
• Three B
• Four C
• Five 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 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

The estimates of the parameters=α and=β are

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

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 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 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