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Essay / Research Paper Abstract
This 3 page paper uses data from 1990 – 1923 to demonstrate the use of regression analysis in order to estimate the time when there would be not deaths from typhoid in Connecticut. The bibliography cites 1 source.
Page Count:
3 pages (~225 words per page)
File: TS14_TEtypreg.rtf
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Unformatted sample text from the term paper:
at the data that was collected in deaths of Typhoid in Connecticut between the years of 1900 and 1923 it is possible to consider the impact that the treatments and
preventive measures as well as general environment impacts were having on the mortality rates. A cursory look at this data may indicate that the disease was being eradicated and that
within a decade it should not be causing any death in the region. In order to assess this we can use a statistical test.
The first stage of the assessment is to determine the hypothesis. H1 = The occurrence and the incident rate of typhoid in Connecticut is dropping at a rate
that will result in the elimination of typhoid as a cause of death within the following decade. H0 = Typhoid will still be a cause of death after the next
decade; it is not falling at a rate that is likely to result in its elimination. The data for the number of death and the total mortality rate has
been collected and regression analysis can be performance least squares methods. This is a form of regression analysis where the data from the past is used to create a foundations
and then the future is predicted by trying to carry on the graph line the existing data used, the least square method seeks to predict that line with the existing
line drawn so that it has the least squares from the data points. This is then carried forward to assess the future values as a forecast. For this to
be used there need to be at least three data point, the higher the number of data points the greater the certainly associated with the regression, here there is the
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