2.11.1 Problems 2.1 Consider the following five observations. You are to do all the parts of this exercise using only a calculator. X 3 2 1 -1 y 4 2 3 1 0 0 Σx = | Σy = | Σ(x − 1) = ہ لیا Σ(x-7)(y₁ - y) = a. Complete the entries in the table. Put the sums in the last row. What are the sample means x and y? b. Calculate b, and by using (2.7) and (2.8) and state their interpretation. c. Compute Σ Σ *y. Using these numerical values, show that Σ(x – F) = 2x – Nx and Σ(x-7)(y-7)= Σxy-№xy. =1 d. Use the least squares estimates from part (b) to compute the fitted values of y, and complete the remainder of the table below. Put the sums in the last row. X₁ 3 x-x 2 1 Calculate the sample variance of y. s= (-3)/(N-1), the sample variance of x, $=(x₁ - x)²/(N-1), the sample covariance between x and y, s,,= (N-1), the sample correlation between x and y, r, s,/(s,s,) and the coefficient of variation of x, CV, = 100(s/x). What is the median, 50th percentile, of x? (₁-3)(x₁ - x)/ = -1 0 Σ(x₁ - x)² = Y₁ 4 2 3 y-y ŷ₁ ê Σ(ν. – 5) = (x-x)(y-y) ê xe 1 0 MW Σy = Σ=Σ = Σ = Σx = e. On graph paper, plot the data points and sketch the fitted regression line ŷ, b₁ + b₂x₁. f. On the sketch in part (e), locate the point of the means (x,y). Does your fitted line pass through that point? If not, go back to the drawing board, literally. g. Show that for these numerical values y = b₁ + b₂. h. Show that for these numerical values y = y, where y = Ey/N. i. Compute ở. j. Compute var (b₂lx) and se(b₂). 2.2 A household has weekly income of $2000. The mean weekly expenditure for households with this income is E(ylx = $2000)=Hy-$2000 = $220, and expenditures exhibit variance var(ylx = $2,000) = $2,000 = $121. yr llu distributed find the probability that a house

MATLAB: An Introduction with Applications
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Author:Amos Gilat
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Chapter1: Starting With Matlab
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Please solve 2.1 in its entirety, thanks!
**2.11.1 Problems**

**2.1 Consider the following five observations. You are to do all the parts of this exercise using only a calculator.**

| x | y | \( x - \bar{x} \) | \( (x - \bar{x})^2 \) | \( y - \bar{y} \) | \( (x - \bar{x})(y - \bar{y}) \) |
|---|---|-----------------|-------------------|----------------|---------------------------|
| 2 | 4 |                 |                   |                |                           |
| 3 | 2 |                 |                   |                |                           |
| 4 | 1 |                 |                   |                |                           |
| 3 | 3 |                 |                   |                |                           |
| 2 | 0 |                 |                   |                |                           |
| \( \Sigma x = \) | \( \Sigma y = \) | \( \Sigma (x - \bar{x}) = \) | \( \Sigma (x - \bar{x})^2 = \) | \( \Sigma (y - \bar{y}) = \) | \( \Sigma (x - \bar{x})(y - \bar{y}) = \) |

**a.** Complete the entries in the table. Put the sums in the last row. What are the sample means \( \bar{x} \) and \( \bar{y} \)?

**b.** Calculate \( b_1 \) and \( b_2 \) using (2.7) and (2.8) and state their interpretation.

**c.** Compute \( \Sigma(y_i - \bar{y})x_i \). Using these numerical values, show that 
\[ \Sigma(x_i - \bar{x})^2 = \Sigma x_i^2 - N\bar{x}^2 \]

**d.** Use the least squares estimates from part (b) to compute the fitted values of \( y \), and complete the information in the table below. Put the sums in the last row.

| \( x_i \) | \( y_i \) | \( \hat{y_i} \) | \( e_i \) | \( e_i^2 \) | \( x_i e_i \) |
|-----------|-----------|---------------|---------|-------------|---------------|
| 2         |
Transcribed Image Text:**2.11.1 Problems** **2.1 Consider the following five observations. You are to do all the parts of this exercise using only a calculator.** | x | y | \( x - \bar{x} \) | \( (x - \bar{x})^2 \) | \( y - \bar{y} \) | \( (x - \bar{x})(y - \bar{y}) \) | |---|---|-----------------|-------------------|----------------|---------------------------| | 2 | 4 | | | | | | 3 | 2 | | | | | | 4 | 1 | | | | | | 3 | 3 | | | | | | 2 | 0 | | | | | | \( \Sigma x = \) | \( \Sigma y = \) | \( \Sigma (x - \bar{x}) = \) | \( \Sigma (x - \bar{x})^2 = \) | \( \Sigma (y - \bar{y}) = \) | \( \Sigma (x - \bar{x})(y - \bar{y}) = \) | **a.** Complete the entries in the table. Put the sums in the last row. What are the sample means \( \bar{x} \) and \( \bar{y} \)? **b.** Calculate \( b_1 \) and \( b_2 \) using (2.7) and (2.8) and state their interpretation. **c.** Compute \( \Sigma(y_i - \bar{y})x_i \). Using these numerical values, show that \[ \Sigma(x_i - \bar{x})^2 = \Sigma x_i^2 - N\bar{x}^2 \] **d.** Use the least squares estimates from part (b) to compute the fitted values of \( y \), and complete the information in the table below. Put the sums in the last row. | \( x_i \) | \( y_i \) | \( \hat{y_i} \) | \( e_i \) | \( e_i^2 \) | \( x_i e_i \) | |-----------|-----------|---------------|---------|-------------|---------------| | 2 |
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