Microsoft Office Tutorials and References
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(b) Create an XY scatterplot of these two sets of data such that:
￿ Top title: RELATIONSHIP BETWEEN AGE AND NUMBER OF
GROWTH RINGS IN PONDEROSA PINE TREES
￿ x-axis title: AGE (years)
￿ y-axis title: NUMBER OF GROWTH RINGS
￿ re-size the chart so that it is 8 columns wide and 25 rows long
￿ delete the legend
￿ delete the gridlines
￿ move the chart below the table
(c)) Create the least-squares regression line for these data on the scatterplot and
add the regression equation to the chart.
(d) Use Excel to run the regression statistics to ﬁnd the equation for the
leastsquares regression line for these data and display the results below the chart
correlation and three decimal places for all the other decimal numbers, including
the coefﬁcients.
(e) Print just the input data and the chart so that this information ﬁts onto one
page. Then, print the regression output table on a separate page so that it ﬁts
onto that separate page.
(f) save the ﬁle as: GROWTH4
(1) What is the correlation coefﬁcient r ?
(2) What is the y-intercept?
(3) What is the slope of the line?
(4) What is the regression equation for these data (use three decimal places
for the y-intercept and the slope)?
(5) Use the regression equation to predict the NUMBER OF GROWTH
RINGS you would expect for a tree that was 20 years old.
2. Suppose that you wanted to study the relationship between the body weight (X)
and the gill weight (Y) of the crab, Pachygrapsus marmoratus . Body weight was
measured in grams (g) while gill weight was measured in milligrams (mg). You
are interested in determining if a heavier crab would require larger gills in order
to efﬁciently exchange oxygen and carbon dioxide with its environment.
Create an Excel spreadsheet and enter the data using BODY WEIGHT as the
independent (predictor) variable, and GILL WEIGHT as the dependent (crite-
rion) variable. You decide to test your Excel skills on a small sample of crabs
using the hypothetical data presented in Fig. 6.31 .
Create an Excel spreadsheet and enter the data using body weight (in grams) as
the independent variable (predictor) and gill weight (in milligrams) as the
dependent variable (criterion).
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