1. Analyze the data in the Excel file. What is the relationship between the Pric
ID: 1146861 • Letter: 1
Question
1. Analyze the data in the Excel file. What is the relationship between the Price of a 2015 used car, and the quantity sold?
a. Does the data describe a Supply curve, Demand curve, or neither?
2. What information is provided by the City population?
a. How might this affect the quantity sold?
b. Can you control for this effect? How?
c. Does your answer to #2 change your answer to #1? How?
3. What value might Q take if the price is $12,000 and the population is 120,000?
Total Quantity Sold in 2015 Used each CityCar price City Population Quantity price price 25000 Population 15600 11000 12000 14000 9900 9600 12000 14000 13500 16000 16000 18000 18000 20000 1400020000 130000 100000 120000 140000 110000 120000 150000 200000 20000 15000 10000 5000 0 0 2000 4000 6000 8000 10000 12000 14000 16000 18000Explanation / Answer
Consider the given problem here if we plot the “Q” and “P” then we will not get any relationship between “P” and “Q” by seeing the fig. So, here to get a proper information we need to perform “regression”, where “Q” be the dependent variable and “P” and “Population size” be the independent variable or factors.
So, after performing the “regression” the estimated model is given below.
=> Q = 15437.36 – (0.7983)*P + 0.0774*PS, where “Q=Quantity sold”, “P=Price” and “PS=Price of used car”.
So, we can see that it’s a “demand curve” as there are negative relationship between “P” and “Q”.
2).
If we go through the data and the estimated equation mentioned above, we can see that as “PS” increases, => “Q” also increases, => there is a direct relationship between “Q” and “PS”.
a).
So, as there is a direct relationship between “Q” and “PS”, => “PS” can positively effect or influence “Q”, => as the “PS” will increase, => the quantity sold will also increases.
b).
Here the estimated equation is given by, “Q = 15437.36 – (0.7983)*P + 0.0774*PS”. So, here to remove the effect of “PS” we can assume that “PS” is fixed at some specified level, => now there are only 2 variables these are “Q” and “P” but still there are negative relationship between them.
c).
We even if we remove the effect of “PS” from the model still it’s a demand curve, as there is a negative relationship between “Q” and “P”. So, our conclusion about the relationship between “P” and “Q” is same.
3).
So, now let’s assume that “P=$12,000” and “PS=120,000”. So, now by putting “P” and “PS” into the estimated equation we can find out the value of “Q” by using the estimated equation.
=> Q = 15437.36 – (0.7983)*P + 0.0774*PS = 15437.36 – (0.7983)*(12,000) + 0.0774*(120,000).
=> Q = 15,437.36 – 291.6 = (15,145.76).
So, the value of “Q” corresponding to “P=12,000” and “PS=120,000”.
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