5
To solve this problem, we need to work through the mean and variance formulas while understanding how replacing one observation affects them. Let's break it down step-by-step:
Given: The original mean and variance for 10 observations are 10 and 2, respectively. An observation \(\alpha\)is replaced by \(\beta\), resulting in a new mean of 10.1 and a new variance of 1.99.
Step 1: Calculate the Original Total
The mean of the original observations is 10. With 10 observations:
\(S = 10 \times 10 = 100\)
Here, \(S\)is the sum of the original 10 observations.
Step 2: Calculate the New Total
After replacing \(\alpha\)with \(\beta\), the new mean becomes 10.1:
\(S - \alpha + \beta = 10.1 \times 10 = 101\)
Thus,
\(100 - \alpha + \beta = 101\)
\(\beta - \alpha = 1 \quad \text{(Equation 1)}\)
Step 3: Calculate the Variance Relationship
The variance formula is:
\(\text{Variance} = \dfrac{\sum{(x_i - \text{mean})^2}}{n}\)
Original variance:
\(\dfrac{\sum(x_i - 10)^2}{10} = 2 \implies \sum(x_i - 10)^2 = 20\)
New variance:
\(\dfrac{\sum(x_i - 10.1)^2}{10} = 1.99 \implies \sum(x_i - 10.1)^2 = 19.9\)
The differences can be written as:
\((100 - \alpha)^2 - 10 \times (10 - 10.1)^2 = \beta^2 - \alpha^2 \implies 19.9 = 20 + \beta^2 - \alpha^2\)
\(\beta^2 - \alpha^2 = -0.1 \quad \text{(Equation 2)}\)
Step 4: Solve Equations 1 and 2
We have:
From the identity \((a - b)(a + b) = a^2 - b^2\), we know:
\((\beta - \alpha)(\beta + \alpha) = -0.1\)
\(1 \cdot (\beta + \alpha) = -0.1 \implies \beta + \alpha = -0.1\)
Thus,
\(\beta + \alpha = 10\)
Conclusion: Based on the calculations, \(\alpha + \beta = 10\).
The correct answer is: 10
