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HSC Commerce (English Medium) 12th Standard Board Exam - Maharashtra State Board Question Bank Solutions for Mathematics and Statistics

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Mathematics and Statistics
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If n = 5, Σx = Σy = 20, Σx2 = Σy2 = 90, Σxy = 76 Find the regression equation of x on y

[11] Linear Regression
Chapter: [11] Linear Regression
Concept: undefined >> undefined

If n = 6, Σx = 36, Σy = 60, Σxy = –67, Σx2 = 50, Σy2 =106, Estimate y when x is 13

[11] Linear Regression
Chapter: [11] Linear Regression
Concept: undefined >> undefined

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The regression equation of x on y is 40x – 18y = 214  ......(i)

The regression equation of y on x is 8x – 10y + 66 = 0  ......(ii)

Solving equations (i) and (ii),

`barx = square`

`bary = square`

∴ byx = `square/square`

∴ bxy = `square/square`

∴ r = `square`

Given variance of x = 9

∴ byx = `square/square`

∴ `sigma_y = square`

[11] Linear Regression
Chapter: [11] Linear Regression
Concept: undefined >> undefined

Choose the correct alternative:

Moving averages are useful in identifying ______.

[12] Time Series
Chapter: [12] Time Series
Concept: undefined >> undefined

The complicated but efficient method of measuring trend of time series is ______

[12] Time Series
Chapter: [12] Time Series
Concept: undefined >> undefined

The simplest method of measuring trend of time series is ______

[12] Time Series
Chapter: [12] Time Series
Concept: undefined >> undefined

The method of measuring trend of time series using only averages is ______

[12] Time Series
Chapter: [12] Time Series
Concept: undefined >> undefined

State whether the following statement is True or False:

The secular trend component of time series represents irregular variations

[12] Time Series
Chapter: [12] Time Series
Concept: undefined >> undefined

State whether the following statement is True or False: 

Moving average method of finding trend is very complicated and involves several calculations

[12] Time Series
Chapter: [12] Time Series
Concept: undefined >> undefined

State whether the following statement is True or False:

Least squares method of finding trend is very simple and does not involve any calculations

[12] Time Series
Chapter: [12] Time Series
Concept: undefined >> undefined

Following table shows the amount of sugar production (in lac tons) for the years 1971 to 1982

Year 1971 1972 1973 1974 1975 1976
Production 1 0 1 2 3 2
Year 1977 1978 1979 1980 1981 1982
Production 4 6 5 1 4 10

Fit a trend line by the method of least squares

[12] Time Series
Chapter: [12] Time Series
Concept: undefined >> undefined

Obtain trend values for data, using 4-yearly centred moving averages

Year 1971 1972 1973 1974 1975 1976
Production 1 0 1 2 3 2
Year 1977 1978 1979 1980 1981 1982
Production 4 6 5 1 4 10
[12] Time Series
Chapter: [12] Time Series
Concept: undefined >> undefined

The following table gives the production of steel (in millions of tons) for years 1976 to 1986.

Year 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986
Production 0 4 4 2 6 8 5 9 4 10 10

Obtain the trend value for the year 1990

[12] Time Series
Chapter: [12] Time Series
Concept: undefined >> undefined

Obtain the trend values for the data, using 3-yearly moving averages

Year 1976 1977 1978 1979 1980 1981
Production 0 4 4 2 6 8
Year 1982 1983 1984 1985 1986  
Production 5 9 4 10 10  
[12] Time Series
Chapter: [12] Time Series
Concept: undefined >> undefined

Use the method of least squares to fit a trend line to the data given below. Also, obtain the trend value for the year 1975.

Year 1962 1963 1964 1965 1966 1967 1968 1969
Production
(million barrels)
0 0 1 1 2 3 4 5
Year 1970 1971 1972 1973 1974 1975 1976  
Production
(million barrels)
6 8 9 9 8 7 10  
[12] Time Series
Chapter: [12] Time Series
Concept: undefined >> undefined

The following table shows the production of gasoline in U.S.A. for the years 1962 to 1976.

Year 1962 1963 1964 1965 1966 1967 1968 1969
Production
(million barrels)
0 0 1 1 2 3 4 5
Year 1970 1971 1972 1973 1974 1975 1976  
Production
(million barrels)
6 7 8 9 8 9 10  
  1. Obtain trend values for the above data using 5-yearly moving averages.
  2. Plot the original time series and trend values obtained above on the same graph.
[12] Time Series
Chapter: [12] Time Series
Concept: undefined >> undefined

Following table shows the all India infant mortality rates (per ‘000) for years 1980 to 2010

Year 1980 1985 1990 1995
IMR 10 7 5 4
Year 2000 2005 2010  
IMR 3 1 0  

Fit a trend line by the method of least squares

Solution: Let us fit equation of trend line for above data.

Let the equation of trend line be y = a + bx   .....(i)

Here n = 7(odd), middle year is `square` and h = 5

Year IMR (y) x x2 x.y
1980 10 – 3 9 – 30
1985 7 – 2 4 – 14
1990 5 – 1 1 – 5
1995 4 0 0 0
2000 3 1 1 3
2005 1 2 4 2
2010 0 3 9 0
Total 30 0 28 – 44

The normal equations are

Σy = na + bΣx

As, Σx = 0, a = `square`

Also, Σxy = aΣx + bΣx2

As, Σx = 0, b =`square`

∴ The equation of trend line is y = `square`

[12] Time Series
Chapter: [12] Time Series
Concept: undefined >> undefined

Obtain trend values for data, using 3-yearly moving averages
Solution:

Year IMR 3 yearly
moving total
3-yearly moving
average

(trend value)
1980 10
1985 7 `square` 7.33
1990 5 16 `square`
1995 4 12 4
2000 3 8 `square`
2005 1 `square` 1.33
2010 0
[12] Time Series
Chapter: [12] Time Series
Concept: undefined >> undefined

Fit equation of trend line for the data given below.

Year Production (y) x x2 xy
2006 19 – 9 81 – 171
2007 20 – 7 49 – 140
2008 14 – 5 25 – 70
2009 16 – 3 9 – 48
2010 17 – 1 1 – 17
2011 16 1 1 16
2012 18 3 9 54
2013 17 5 25 85
2014 21 7 49 147
2015 19 9 81 171
Total 177 0 330 27

Let the equation of trend line be y = a + bx   .....(i)

Here n = `square` (even), two middle years are `square` and 2011, and h = `square`

The normal equations are Σy = na + bΣx

As Σx = 0, a = `square`

Also, Σxy = aΣx + bΣx2

As Σx = 0, b = `square`

Substitute values of a and b in equation (i) the equation of trend line is `square`

To find trend value for the year 2016, put x = `square` in the above equation.

y = `square`

[12] Time Series
Chapter: [12] Time Series
Concept: undefined >> undefined

Complete the table using 4 yearly moving average method.

Year Production 4 yearly
moving
total
4 yearly
centered
total
4 yearly centered
moving average
(trend values)
2006 19  
    `square`    
2007 20   `square`
    72    
2008 17   142 17.75
    70    
2009 16   `square` 17
    `square`    
2010 17   133 `square`
    67    
2011 16   `square` `square`
    `square`    
2012 18   140 17.5
    72    
2013 17   147 18.375
    75    
2014 21  
       
2015 19  
[12] Time Series
Chapter: [12] Time Series
Concept: undefined >> undefined
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