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HSC Commerce (Marathi Medium) १२ वीं कक्षा - Maharashtra State Board Important Questions for Mathematics and Statistics

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Mathematics and Statistics
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Find the equation of the line of regression of Y on X for the following data:

n = 8, `sum(x_i - barx).(y_i - bary) = 120, barx = 20, bary = 36, sigma_x = 2, sigma_y = 3`

Appears in 1 question paper
Chapter: [11] Linear Regression
Concept: Lines of Regression of X on Y and Y on X Or Equation of Line of Regression

Choose the correct alternative:

If byx < 0 and bxy < 0, then r is ______

Appears in 1 question paper
Chapter: [11] Linear Regression
Concept: Properties of Regression Coefficients

Choose the correct alternative:

If the lines of regression of Y on X is y = `x/4` and X on Y is x = `y/9 + 1` then the value of r is

Appears in 1 question paper
Chapter: [11] Linear Regression
Concept: Lines of Regression of X on Y and Y on X Or Equation of Line of Regression

State whether the following statement is True or False:

The following data is not consistent: byx + bxy =1.3 and r = 0.75

Appears in 1 question paper
Chapter: [11] Linear Regression
Concept: Properties of Regression Coefficients

If n = 5, ∑xy = 76, ∑x2 = ∑y2 = 90, ∑x = 20 = ∑y, the covariance = ______

Appears in 1 question paper
Chapter: [11] Linear Regression
Concept: Properties of Regression Coefficients

If the regression equations are 8x – 10y + 66 = 0 and 40x – 18y = 214, the mean value of y is ______

Appears in 1 question paper
Chapter: [11] Linear Regression
Concept: Lines of Regression of X on Y and Y on X Or Equation of Line of Regression

Given the following information about the production and demand of a commodity.
Obtain the two regression lines:

  ADVERTISEMENT (x)
(₹ in lakhs)
DEMAND (y)
(₹ in lakhs)
Mean 10 90
Variance 9 144

Coefficient of correlation between x and y is 0.8.
What should be the advertising budget if the company wants to attain the sales target of ₹ 150 lakhs?

Appears in 1 question paper
Chapter: [11] Linear Regression
Concept: Properties of Regression Coefficients

Two samples from bivariate populations have 15 observations each. The sample means of X and Y are 25 and 18 respectively. The corresponding sum of squares of deviations from means are 136 and 148 respectively. The sum of product of deviations from respective means is 122. Obtain the regression equation of x on y

Appears in 1 question paper
Chapter: [11] Linear Regression
Concept: Lines of Regression of X on Y and Y on X Or Equation of Line of Regression

For a certain bivariate data of a group of 10 students, the following information gives the internal marks obtained in English (X) and Hindi (Y):

  X Y
Mean 13 17
Standard Deviation 3 2

If r = 0.6, Estimate x when y = 16 and y when x = 10

Appears in 1 question paper
Chapter: [11] Linear Regression
Concept: Properties of Regression Coefficients
x y `x - barx` `y - bary` `(x - barx)(y - bary)` `(x - barx)^2` `(y - bary)^2`
1 5 – 2 – 4 8 4 16
2 7 – 1 – 2 `square` 1 4
3 9 0 0 0 0 0
4 11 1 2 2 4 4
5 13 2 4 8 1 16
Total = 15 Total = 45 Total = 0 Total = 0 Total = `square` Total = 10 Total = 40

Mean of x = `barx = square`

Mean of y = `bary = square`

bxy = `square/square`

byx = `square/square`

Regression equation of x on y is `(x - barx) = "b"_(xy)  (y - bary)`

∴ Regression equation x on y is `square`

Regression equation of y on x is `(y - bary) = "b"_(yx)  (x - barx)`

∴ Regression equation of y on x is `square`

Appears in 1 question paper
Chapter: [11] Linear Regression
Concept: Properties of Regression Coefficients

For certain bivariate data on 5 pairs of observations given:

∑x = 20, ∑y = 20, ∑x2 = 90, ∑y2 = 90, ∑xy = 76 then bxy = ______.

Appears in 1 question paper
Chapter: [11] Linear Regression
Concept: Lines of Regression of X on Y and Y on X Or Equation of Line of Regression

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

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

Fit the trend line to the above data by the method of least squares.

Appears in 1 question paper
Chapter: [11] Linear Regression
Concept: The Method of Least Squares

Which of the following can’t be a component of a time series?

Appears in 1 question paper
Chapter: [12] Time Series
Concept: Components of a Time Series

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

Appears in 1 question paper
Chapter: [12] Time Series
Concept: Components of a Time Series

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

Appears in 1 question paper
Chapter: [12] Time Series
Concept: Measurement of Secular Trend

State whether the following statement is True or False: 

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

Appears in 1 question paper
Chapter: [12] Time Series
Concept: Measurement of Secular Trend

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

Appears in 1 question paper
Chapter: [12] Time Series
Concept: Measurement of Secular Trend

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  
Appears in 1 question paper
Chapter: [12] Time Series
Concept: Measurement of Secular Trend

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  
Appears in 1 question paper
Chapter: [12] Time Series
Concept: Measurement of Secular Trend

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  
Appears in 1 question paper
Chapter: [12] Time Series
Concept: Measurement of Secular Trend
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