Below is data collected over 6 specific years. The data collected is the Consumer Price Index (CPI) and the cost of tuna. We would like to build a model using the CPI to predict the cost of tuna in a given year. Year 1960 1973 1986 1995 2002 2003 CPI (x) 30.2 48.3 112.3 162.2 191.9 197.8 tuna(y) 0.15 0.35 1.00 1.25 1.75 2.00 In the year 2000, the CPI was 187.1. Predict the cost of tuna that year. Provide a prediction interval. Don’t forget to make a concluding statement in the context of the problem.
Below is data collected over 6 specific years. The data collected is the Consumer Price Index (CPI) and the cost of tuna. We would like to build a model using the CPI to predict the cost of tuna in a given year. Year 1960 1973 1986 1995 2002 2003 CPI (x) 30.2 48.3 112.3 162.2 191.9 197.8 tuna(y) 0.15 0.35 1.00 1.25 1.75 2.00 In the year 2000, the CPI was 187.1. Predict the cost of tuna that year. Provide a prediction interval. Don’t forget to make a concluding statement in the context of the problem.
Chapter6: Exponential And Logarithmic Functions
Section6.8: Fitting Exponential Models To Data
Problem 3TI: Table 6 shows the population, in thousands, of harbor seals in the Wadden Sea over the years 1997 to...
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Below is data collected over 6 specific years. The data collected is the Consumer Price Index (CPI) and the cost of tuna. We would like to build a model using the CPI to predict the cost of tuna in a given year.
|
Year
|
1960 |
1973 |
1986 |
1995 |
2002 |
2003 |
|
CPI (x)
|
30.2 |
48.3 |
112.3 |
162.2 |
191.9 |
197.8 |
|
tuna(y) |
0.15 |
0.35 |
1.00 |
1.25 |
1.75 |
2.00 |
In the year 2000, the CPI was 187.1. Predict the cost of tuna that year. Provide a prediction interval. Don’t forget to make a concluding statement in the context of the problem.
-Notice that the margin of error in the prediction interval is fairly high (about 25% of the point estimate). Why is this? What could we do to make our prediction more accurate?
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