346 Statistical Methods
c. Create a scatter plot of mortality
versus temperature and add a linear
trend line to the plot, showing both the
R^2 value and the regression equation.
d. Calculate the regression statistics for
the new data set.
e. Create scatter plots of the residuals of
the regression equation versus tem-
perature and the predicted values.
Also create a normal probability plot
of the residuals.
f. Calculate the Pearson and Spearman
correlation coeffi cients, including the
p values.
g. Save your changes to the workbook
and write a report summarizing your
results, including a description of the
diagnostic tests you performed. How
does this regression compare with the
regression you performed earlier that
included the possible outlier? How do
the diagnostic plots compare?- You’ve been given an Excel workbook
containing nutritional information on 10
wheat products. Perform the following
analysis:
a. Open the Wheat workbook from the
Chapter08 folder and save it as Wheat
Regression Analysis.
b. Plot Calories versus ServingGrams,
adding a regression line, equation,
and R^2 value to the plot. How does
the serving size (in grams) predict
the calories of the different wheat
products?
c. Compute Pearson’s correlation and
the corresponding p value between
Calories and ServingGrams.
d. Use the Data Analysis ToolPak to cal-
culate the statistics for the regression
equation.
e. Create diagnostic plots of residuals
versus ServingGrams, and the normal
probability plot of the residuals. Do
the regression assumptions seem to be
satisfi ed?
f. In the plot of residuals versus pre-
dicted values, label each point with
the food type (pretzel, bagel, bread,
etc). Where do the residuals for the
breads appear?
g. Breads are often low in calories be-
cause of high moisture content. One
way of removing the moisture content
from the equation is to create a new
variable that sums up the total of the
nutrient weights. With this in mind,
create a new variable, total, which
is the sum of the weights of carbo-
hydrates, proteins, and fats. From this
total subtract the value of the Fiber
variable since fi ber does not contrib-
ute to the calorie total. Plot Calories
versus Total on a new chart sheet.
h. Redo your regression equation, re-
gressing the Calories variable on the
new variable Total. How does the di-
agnostic plot of residuals versus pre-
dicted values compare to the earlier
plot? How do the R^2 values compare?
Where are the residuals for the bread
values located?
i. Save your changes to the workbook
and write a report summarizing your
observations.- Continue to investigate the nutritional
data in the Wheat workbook by perform-
ing the following analysis:
a. Open the Wheat workbook from the
Chapter08 folder and save it as Wheat
Correlation Matrix.
b. Create scatter plot and correlation ma-
trices (Pearson correlation only) for
the variables serving grams, calories,
protein, carbohydrate, and fat.
c. Why is fat so weakly related to the
other variables? Given that fat is
supposed to be very important in
calories, why is the correlation so
weak here?
d. Would the relationship between the
fat and calories variables be stronger