Question # 1

The systematic components of time series which follow regular pattern of variations are called:

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Noise

Signal

Additive model

Multiplicative model

Which one is a rough and crude method for measuring secular trend ?

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free hand curve method

semi average method

moving averages method

least square method

For a least squares linear trend Y = a + bX

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ΣY = ΣY

ΣY = 0

ΣY > ΣY

None of them

The rise and fall of a time series periods longer than one- year is called.

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Secular trend

Seasonal variation

Cyclical variation

Irregular variation

The trend values in freehand curve method are obtained by:

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Equation of straight line

Second degree parabola

Signal

Graph

The additive model of the time series is:

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Y = T + S + C + I

TSCI

Y = a + bX

Y = a + bX + cX²

Methods of semi-averages gives an

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accurate result

objective result

authentic result

none of these

The straight line is fitted to a time series when the movements in the time series are

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linear

quadratic

cubic

constant

For a least squares linear trend ŷ = a + bx, the Σ(y-ŷ)² = 0 when

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all the y-values lie on the line

all the y-values are positive

all the y-+values lie above the line

none of these

The secular trend is measured by the method of semi-averages when

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time series contains yearly values

trend is linear

time series contains odd number of values

none of these

For a least squares line trend Y = a + bx, the b is the:

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Intercept

Slope

Variable

Trend

The sum of deviations=Σ(y-ŷ) =

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0

1

10

-1

The unsystematic sequence which follows irregular pattern of variations is called:

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Noise

Signal

Linear

Non-linear

The elimination or addition of a few more time periods may change its

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speed

value

direction

none of these

The method of least square gives too much weight to extremely large deviations from the

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population

parameter

sample

trend

Sum of squares of residuals is denoted by

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∑e

∑e²

∑e³

∑e⁴

The secular trend is measured by the method of semi-averages when:

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Time series contains yearly value

Trend is linear

Time series contains odd number of values

None of them

For a least squares linear trend=ŷ= a + b x,

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Σy <Σŷ

Σŷ = 0

Σy =Σŷ

none of these

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