rmk

1. 80 years of Dow Jones
Industrial
BY: FAITH ADEFARAKAN

4. regular Exponential

5. Power

6. 1. Describe the association between “DJIA price” and “Years Since 1930” 1. Describe the association between “DJIA price” and
“Years Since 1930”. 1. Describe the association between “DJIA price” and “Years Since 1930”.
There association is a positive exponential relationship between the years since and the
dow price.
2. What is the equation for your linear model? (Use descriptive variables)
Dow Price = 125.3(years)-2.4425x10^05
3. Interpret the slope of the line in context.
As the years increase the price goes up by 125 per year. The slope is steep
4. Does the y-intercept of your model have a meaningful interpretation or is it just
a hypothetical base value? Explain.
The y intercept DOES NOT have a meaningful interpretation because the R^2 is
63% which means that the y intercept has little to no association to the years
since.

7. 5. Look at the residuals plot for your linear model. Do you have any concerns
about predictions made by your model? Explain.
Yes. I’m concerned that the data being used isn’t descriptive enough .
6. What is the equation of your new model? (Use descriptive variables)
Y hat=.06234(year)-116
7. Interpret the slope of the line in context.
As the year increases the price goes up .06234.
8. The y-intercept of your model have a meaningful
interpretation? Explain.
The y-intercept has a meaningful interpretation because there is a strong
correlation and association ,because of R^2.
9. The residuals plot for your transformed model still doesn’t look perfect, but has
it improved? How do you feel about the appropriateness of your new model?
The residual plot has improved from the original graph because there is a
clearer correlation.
10. What is the correlation for your transformed data? What does this indicate
about the association?
The correlation is roughly linear but also positive. This indicates that the
exponential graph has the best "line of best fit".
11. What is R2 for your transformed data? Interpret this value in context.
R squared is 0.94 which is also 94%. This means that the natural log of the dow
price and the years since have a strong correlation and association.
12. Use your model to make a prediction about the Dow price in July of 2012.

8. Y hat= .06234(2012)-116=9.42808
E^9.42808=12432.63315
13. You will most likely retire sometime between 2040 and 2050. What does your
model predict for the Dow price in 2045? Comment on the appropriateness of
this prediction.
Y hat= .06234(2045)-116= 11.4853
E^11.4853=97275.2628514. What is the equation of the exponential model that Microsoft Excel fit to the
original data?
Y hat=.06234(year)-116
15. Use the exponential model to make a prediction about the Dow price in 2012.
Compare it to the prediction made by your model. Are they close?
Y hat= .06234(2012)-116=9.42808
E^9.42808=12432.6331
16. Calculate the y-intercept of your model and the y-intercept of the exponential
model. Are they close? Are these predictions lower or higher than the actual
Dow price on 2012?
Y- intercept for model a is -2.44e
Y-intercept for model b is -116.
The prediction for model B is lower than the predictions for model A.