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Online Tests
Statistics Ics Part 2 Chapter 7 Online Test MCQs With Answers
Question # 1
ŷ=a+bx, this line will be called least squares line if it makes=Σ(y-a-bx)2
Choose an answer
maximum
constant
minimum
variable
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Question # 2
Sum of squares of residuals is denoted by
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∑
e
∑
e
2
∑
e
3
∑
e
4
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Question # 3
The least squares estimates are unbiased estimates of the
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statistic
time series
parameters
variance
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Question # 4
For a least squares linear trend Y = a + bX
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ΣY = ΣY
ΣY = 0
ΣY > ΣY
None of them
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Question # 5
In the measurement of secular trend the moving averages
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give the trend in a straight line
measure the seasonal variations
smoothes out a time series
measure irregular fluctuations
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Question # 6
In the measurement of secular trend the moving averages:
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Give the trend in a straight line
Measure the seasonal variations
Smooth out a time series
None of these
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Question # 7
Methods of semi-averages gives an
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accurate result
objective result
authentic result
none of these
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Question # 8
The basic components of a time series are:
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2
3
4
5
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Question # 9
Increase the number of patients in the hospital due to heel stock is:
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Seasonal trend
Secular trend
Cyclical movements
Irregular variation
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Question # 10
The graph of time series is called:
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Histogram
Historigram
Straight line
Ogive
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Question # 11
For a least squares line trend Y = a + bx, the b is the:
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Intercept
Slope
Variable
Trend
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Question # 12
The equation of the quadratic (parabolic) trend is
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ŷ=a+bx
ŷ=a+by
ŷ=a+bΣx+cΣx
2
ŷ=a+bx+cx
2
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Question # 13
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
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Question # 14
A business cycle has
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one phase
two phases
three phases
four phases
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Question # 15
The sum of deviations=Σ(y-ŷ) =
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0
1
10
-1
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Question # 16
The multiplicative time series model is:
Choose an answer
Y = T + S + C + I
TSCI
Y = a + bX
Y = a + bX + cX
2
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Question # 17
In moving average method, we cannot find the trend values of some:
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Middle periods
End periods
Starting periods
Between extreme periods
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