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Chapters
Chapter 1.2: Matrices
Chapter 1.3: Differentiation
Chapter 1.4: Applications of Derivatives
Chapter 1.5: Integration
Chapter 1.6: Definite Integration
Chapter 1.7: Application of Definite Integration
Chapter 1.8: Differential Equation and Applications
Chapter 2.1: Commission, Brokerage and Discount
Chapter 2.2: Insurance and Annuity
Chapter 2.3: Linear Regression
Chapter 2.4: Time Series
Chapter 2.5: Index Numbers
Chapter 2.6: Linear Programming
Chapter 2.7: Assignment Problem and Sequencing
Chapter 2.8: Probability Distributions

Chapter 2: Time Series
SCERT Maharashtra Question Bank solutions for 12th Standard HSC Mathematics and Statistics (Commerce) Maharashtra State Board 2022 Chapter 2 Time Series Q.1
MCQ [1 Mark]
Choose the correct alternative:
Which of the following can’t be a component of a time series?
Seasonality
Cyclical
Trend
Mean
Choose the correct alternative:
Which component of time series refers to erratic time series movements that follow no recognizable or regular pattern?
Trend
Seasonal
Cyclical
Irregular
Choose the correct alternative:
The following trend line equation was developed for annual sales from 1984 to 1990 with 1984 as base or zero year.
Y = 500 + 60X (in 1000 ₹). The estimated sales for 1984 (in 1000 ₹) is
500
560
1,040
1,100
Choose the correct alternative:
An overall upward or downward pattern in an annual time series would be contained in which component of the times series?
Trend
Cyclical
Irregular
Seasonal
Choose the correct alternative:
Moving averages are useful in identifying
Seasonal component
Irregular component
Trend component
cyclical component
SCERT Maharashtra Question Bank solutions for 12th Standard HSC Mathematics and Statistics (Commerce) Maharashtra State Board 2022 Chapter 2 Time Series Q.2
Fill in the blanks [1Markl]
______ components of time series is indicated by a smooth line
______ component of time series is indicated by periodic variation year after year.
The complicated but efficient method of measuring trend of time series is ______
The simplest method of measuring trend of time series is ______
The method of measuring trend of time series using only averages is ______
SCERT Maharashtra Question Bank solutions for 12th Standard HSC Mathematics and Statistics (Commerce) Maharashtra State Board 2022 Chapter 2 Time Series Q.3
State whether the following statement is True or False:
The secular trend component of time series represents irregular variations
True
False
State whether the following statement is True or False:
Seasonal variation can be observed over several years
True
False
State whether the following statement is True or False:
Cyclical variation can occur several times in a year
True
False
State whether the following statement is True or False:
Moving average method of finding trend is very complicated and involves several calculations
True
False
State whether the following statement is True or False:
Least squares method of finding trend is very simple and does not involve any calculations
True
False
SCERT Maharashtra Question Bank solutions for 12th Standard HSC Mathematics and Statistics (Commerce) Maharashtra State Board 2022 Chapter 2 Time Series Q.4
Solve the followoing problems. [4 Marks]
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
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 |
The following table gives the production of steel (in millions of tons) for years 1976 to 1986.
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 |
Fit a trend line by the method of least squares. Also, obtain the trend value for the year 1990
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 |
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 |
The following table shows the production of gasoline in U.S.A. for the years 1962 to 1976.
Obtain trend values for the above data using 5-yearly moving averages.
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 |
SCERT Maharashtra Question Bank solutions for 12th Standard HSC Mathematics and Statistics (Commerce) Maharashtra State Board 2022 Chapter 2 Time Series Q.5
Activity based question [4 Mark]
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`
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 | – | – |
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`
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 | – | – |
Chapter 2: Time Series

SCERT Maharashtra Question Bank solutions for 12th Standard HSC Mathematics and Statistics (Commerce) Maharashtra State Board 2022 chapter 2 - Time Series
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Concepts covered in 12th Standard HSC Mathematics and Statistics (Commerce) Maharashtra State Board 2022 chapter 2 Time Series are Introduction to Time Series, Uses of Time Series Analysis, Components of a Time Series, Mathematical Models, Measurement of Secular Trend.
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