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If the mean of a set of observations `x_(1),x_(2), …,x_(n)" is " bar(X)`, then the mean of the observations `x_(i) +2i , i=1, 2, ..., n` is

A

`bar(X) +2`

B

`bar(X) +2n`

C

`bar(X)+(n+1)`

D

`X+n`

Text Solution

AI Generated Solution

The correct Answer is:
To find the mean of the observations \( x_i + 2i \) for \( i = 1, 2, \ldots, n \), we can follow these steps: ### Step 1: Understand the Mean of Original Observations Given that the mean of the observations \( x_1, x_2, \ldots, x_n \) is \( \bar{X} \), we can express this mathematically: \[ \bar{X} = \frac{x_1 + x_2 + \ldots + x_n}{n} \] ### Step 2: Calculate the New Observations The new observations are given by \( x_i + 2i \) for \( i = 1, 2, \ldots, n \). Therefore, we can write: \[ \text{New Observations} = (x_1 + 2 \cdot 1), (x_2 + 2 \cdot 2), \ldots, (x_n + 2n) \] ### Step 3: Find the Sum of the New Observations The sum of the new observations can be expressed as: \[ \text{Sum} = (x_1 + 2 \cdot 1) + (x_2 + 2 \cdot 2) + \ldots + (x_n + 2n) \] This can be simplified to: \[ \text{Sum} = (x_1 + x_2 + \ldots + x_n) + 2(1 + 2 + \ldots + n) \] ### Step 4: Use the Formula for the Sum of the First n Natural Numbers The sum of the first \( n \) natural numbers \( 1 + 2 + \ldots + n \) is given by the formula: \[ 1 + 2 + \ldots + n = \frac{n(n + 1)}{2} \] Thus, we can substitute this into our sum: \[ \text{Sum} = (x_1 + x_2 + \ldots + x_n) + 2 \cdot \frac{n(n + 1)}{2} \] This simplifies to: \[ \text{Sum} = (x_1 + x_2 + \ldots + x_n) + n(n + 1) \] ### Step 5: Calculate the Mean of the New Observations Now, we can find the mean of the new observations: \[ \text{Mean} = \frac{\text{Sum}}{n} = \frac{(x_1 + x_2 + \ldots + x_n) + n(n + 1)}{n} \] Substituting \( \bar{X} \) for the sum of the original observations: \[ \text{Mean} = \frac{n \bar{X} + n(n + 1)}{n} \] This simplifies to: \[ \text{Mean} = \bar{X} + (n + 1) \] ### Final Answer Thus, the mean of the observations \( x_i + 2i \) is: \[ \bar{X} + (n + 1) \]
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Knowledge Check

  • The geometric mean of the observations x_(1),x_(2)x_(3)…x_(n) is G. The geometric mean of the observations y_(1), y_(2), y_(3).... Y_(n) is G_(2) . The geometric mean of the observations (x_(1))/(y_(1)),(x_(1))/(y_(2)),(x_(3))/(y_(3))…(x_(n))/(y_(n)) is

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    A
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