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

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Solve the following differential equation:

(x2 – y2)dx + 2xy dy = 0

[8] Differential Equation and Applications
Chapter: [8] Differential Equation and Applications
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Let p ∧ (q ∨ r) ≡ (p ∧ q) ∨ (p ∧ r). Then, this law is known as ______.

[1] Mathematical Logic
Chapter: [1] Mathematical Logic
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Without using truth table, show that

p ↔ q ≡ (p ∧ q) ∨ (~p ∧ ~q)

[1] Mathematical Logic
Chapter: [1] Mathematical Logic
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Without using truth table, show that

p ∧ [(~ p ∨ q) ∨ ~ q] ≡ p

[1] Mathematical Logic
Chapter: [1] Mathematical Logic
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Without using truth table, show that

~ [(p ∧ q) → ~ q] ≡ p ∧ q

[1] Mathematical Logic
Chapter: [1] Mathematical Logic
Concept: undefined >> undefined

Without using truth table, show that

~r → ~ (p ∧ q) ≡ [~ (q → r)] → ~ p

[1] Mathematical Logic
Chapter: [1] Mathematical Logic
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Without using truth table, show that

(p ∨ q) → r ≡ (p → r) ∧ (q → r)

[1] Mathematical Logic
Chapter: [1] Mathematical Logic
Concept: undefined >> undefined

Using the algebra of statement, prove that

[p ∧ (q ∨ r)] ∨ [~ r ∧ ~ q ∧ p] ≡ p

[1] Mathematical Logic
Chapter: [1] Mathematical Logic
Concept: undefined >> undefined

Using the algebra of statement, prove that

(p ∧ q) ∨ (p ∧ ~ q) ∨ (~ p ∧ ~ q) ≡ (p ∨ ~ q)

[1] Mathematical Logic
Chapter: [1] Mathematical Logic
Concept: undefined >> undefined

Using the algebra of statement, prove that (p ∨ q) ∧ (~ p ∨ ~ q) ≡ (p ∧ ~ q) ∨ (~ p ∧ q).

[1] Mathematical Logic
Chapter: [1] Mathematical Logic
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For the following bivariate data obtain the equations of two regression lines:

X 1 2 3 4 5
Y 5 7 9 11 13
[11] Linear Regression
Chapter: [11] Linear Regression
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From the data of 20 pairs of observations on X and Y, following results are obtained.

`barx` = 199, `bary` = 94,

`sum(x_i - barx)^2` = 1200, `sum(y_i - bary)^2` = 300,

`sum(x_i - bar x)(y_i - bar y)` = –250

Find:

  1. The line of regression of Y on X.
  2. The line of regression of X on Y.
  3. Correlation coefficient between X and Y.
[11] Linear Regression
Chapter: [11] Linear Regression
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Given the following data, obtain a linear regression estimate of X for Y = 10, `bar x = 7.6, bar y = 14.8, sigma_x = 3.2, sigma_y = 16` and r = 0.7

[11] Linear Regression
Chapter: [11] Linear Regression
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bYX is ______.

[11] Linear Regression
Chapter: [11] Linear Regression
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Obtain the trend line for the above data using 5 yearly moving averages.

[12] Time Series
Chapter: [12] Time Series
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The data obtained on X, the length of time in weeks that a promotional project has been in progress at a small business, and Y, the percentage increase in weekly sales over the period just prior to the beginning of the campaign.

X 1 2 3 4 1 3 1 2 3 4 2 4
Y 10 10 18 20 11 15 12 15 17 19 13 16

Find the equation of the regression line to predict the percentage increase in sales if the campaign has been in progress for 1.5 weeks.

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

If for bivariate data `bar x = 10, bar y = 12,` v(x) = 9, σy = 4 and r = 0.6 estimate y, when x = 5.

[11] Linear Regression
Chapter: [11] Linear Regression
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Fit a trend line to the data in Problem 4 above by the method of least squares. Also, obtain the trend value for the index of industrial production for the year 1987.

[12] Time Series
Chapter: [12] Time Series
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The equation of the line of regression of y on x is y = `2/9` x and x on y is x = `"y"/2 + 7/6`.
Find (i) r,  (ii) `sigma_"y"^2 if sigma_"x"^2 = 4`

[11] Linear Regression
Chapter: [11] Linear Regression
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Identify the regression equations of x on y and y on x from the following equations, 2x + 3y = 6 and 5x + 7y − 12 = 0

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