The attached graph shows the required curves to be drawn. One of the curves is called the Marginal Revenue Curve.
<h3>What is a marginal revenue curve?</h3>
At the market price, the marginal revenue curve is a horizontal line, suggesting completely elastic demand, and it is equal to the demand curve.
Monopoly occurs when one corporation is the exclusive vendor of a distinct product in the market.
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Full Question:
The graph shows the market for smart rackets.
Suppose the profit-maximizing output is 160,000 smart rackets.
Draw the firm's marginal revenue curve. Label it MR.
Draw the firm's marginal cost curve. Label it MC.
Draw a point at the profit-maximizing output and price.
Draw a shape to show the firm's economic profit. Label it.
The length of the long leg of the triangle is 144 units
<h3>Pythagoras theorem</h3>
Pythagoras theorem is used to solve the sides of a right angle triangle and can be represented as follows;
where
c = hypotenuse
a and b are the other legs.
Therefore,
145² - 17² = b²
b² = 21025 - 289
b² = 20736
b = √20736
b = 144
Therefore, the length of the longer leg of the triangle is 144 units
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Answer:
I used the function 1-proportion z-interval on the calculator, where I inputted
- Successes(x) = 64
- Sample size(n) = 593
- Confidence Level(C level) = 0.99
It would result in zInterval_1Prop 64,593,0.99: stat.results, where the values are shown below as:
- Lower bound (CLower) = 0.075105
- Upper bound (CUpper) = 0.140747
- test statistic (p^) = 0.107926
- Margin of error (ME) = 0.032821
Therefore, the 99% confidence interval would be around 0.11 ± 0.03 or range from 0.08 to 0.14.
<em><u>Note: not sure if this is correct</u></em><em> O_o</em>
Based on the information given, it should be noted that the slope cannot be interpreted as the equation makes no sense for the model.
<h3>
Interpretation of the slope.</h3>
From the information given, the explanatory variable x was the year that the observations were taken.
In this case, the values are the integer number between 1975 and 1986. The y-intercept of the equation makes no sense for the prediction as it's not in the range of the explanatory data.
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