Let's re-evaluate the calculation step-by-step to ensure accuracy.

Given:
- Intercept (\(\beta_0\)) = 2.0323
- regprc (\(\beta_1\)) = 3.0296
- ecoprc (\(\beta_2\)) = -2.9397
- inseason (\(\beta_3\)) = -0.1580

Values provided:
- regprc = 1.49
- ecoprc = 2.11
- inseason = 1

The regression equation is:
\[ \text{eco\_lbs} = \beta_0 + \beta_1 \times \text{regprc} + \beta_2 \times \text{ecoprc} + \beta_3 \times \text{inseason} \]

Substituting the values:

\[ \text{eco\_lbs} = 2.0323 + 3.0296 \times 1.49 + (-2.9397) \times 2.11 + (-0.1580) \times 1 \]

Now let's calculate step-by-step:

1. \( 3.0296 \times 1.49 = 4.511504 \)
2. \( -2.9397 \times 2.11 = -6.198807 \)
3. \( -0.1580 \times 1 = -0.1580 \)

Summing these up:

\[ 2.0323 + 4.511504 - 6.198807 - 0.1580 = 2.0323 + 4.511504 - 6.198807 - 0.1580 = 0.186997 \]

It appears I miscalculated. Let's correct it and check again to ensure we have the precise value:

1. \( 3.0296 \times 1.49 = 4.511504 \)
2. \( -2.9397 \times 2.11 = -6.197867 \)
3. \( -0.1580 \times 1 = -0.1580 \)

Summing these up:

\[ 2.0323 + 4.511504 - 6.197867 - 0.1580 = 0.187937 \]

Therefore, the corrected predicted household demand for organic apples is approximately **0.19 pounds**.

I apologize for the error in my previous calculation. 

Would you like any more details or have any further questions?

Here are some more questions you might find interesting:

1. How do you interpret the coefficients of the regression model?
2. What does the R-squared value indicate in this context?
3. How would the demand change if organic apples cost 1.50 USD per pound instead?
4. What is the significance of the p-values in the regression output?
5. How can we assess the fit of this regression model?

**Tip:** When performing regression analysis, ensure each calculation step is carefully checked for accuracy to avoid errors in the final prediction.

Explore the corrected prediction of household demand for organic apples using regression analysis. Step-by-step calculation and interpretation of coefficients included. Learn about the impact of cost changes on demand.

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