Data Analysis with Microsoft Excel: Updated for Office 2007

(Tuis.) #1

350 Statistical Methods


the correlation between the month
number and the average draft number.
How do the values of the correlation
in this analysis compare with those of
the correlation you performed earlier?
f. Create a scatter plot of average draft
number versus month number. Add a
trend line and include the regression
equation and R^2 value. How much
of the variability in the average draft
number per month is explained by the
month?
g. Save your changes to the workbook
and write a report summarizing your
conclusions. Which analysis (looking
at daily values or looking at monthly
averages) better describes any prob-
lem with the draft lottery?


  1. The Emerald health care providers
    claim that components of their health
    plan cause it to rise signifi cantly more
    slowly than overall health costs. You
    decide to investigate to see whether
    there is evidence for Emerald’s claim.
    You have recorded Emerald costs over
    the past seven years, along with the
    consumer price index (CPI) for all urban
    consumers and the medical component
    of the CPI.
    a. Open the Emerald workbook from
    the Chapter08 folder and save it as
    Emerald Regression Analysis.
    b. Using the Analysis ToolPak’s Regres-
    sion command, calculate the regres-
    sion equation for each of the three
    price indexes against the year vari-
    able. What are the values for the three
    slopes? Express the slope in terms
    of the increase in the index per year.
    How does Emerald’s change in cost
    compare to the other two indexes?
    c. Look at the 95% confi dence intervals
    for the three slopes. Do the confi dence
    intervals overlap? Does there appear
    to be a signifi cant difference in the
    rate of increase under the Emerald


plan as compared to the increases
under the other two indexes?
d. Summarize your conclusions. Do you
see evidence to substantiate Emerald’s
claim?
e. Save your changes and write a report
summarizing your observations.


  1. The Teacher workbook contains data on
    the relationship between teachers’ sala-
    ries and the spending on public schools
    per pupil in 1985. Perform the following
    analysis on this data set:
    a. Open the Teacher workbook from
    the Chapter08 folder and save it as
    Teacher Salary Analysis.
    b. Create a scatter plot of spending per
    pupil versus teacher salary. Add a
    trend line containing the R^2 value and
    regression to the plot.
    c. Compute the regression statistics for
    the data, and then create the diagnos-
    tic plots discussed in this chapter. Is
    there any evidence of a problem in
    the diagnostic plots?
    d. Copy the spending per pupil versus
    teacher salary scatter plot to a new
    chart sheet and then break down the
    points in the plot on the basis of the
    values of the area variable. For each
    of the three series in the chart, add a
    linear trend line and compute the
    R^2 value and regression equation. How
    do the least-squares lines compare
    among the three regions? What do you
    think accounts for any difference in
    the trend lines?
    e. Redo the regression statistics, per-
    forming three regressions, one for
    each of the three areas in the data set.
    Compare the regression equations.
    What are the 95% confi dence inter-
    vals for the slope parameters in the
    three areas?
    f. Save your changes to the workbook
    and write a report summarizing your
    observations.

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