Sale!

Homework 4 of STAT 3355 Data Analysis for Statisticians & Actuaries solved

Original price was: $35.00.Current price is: $30.00. $25.50

Category:

Description

5/5 - (9 votes)

Let’s work on the UScereal dataset in the package UsingR. You can use the following
code to load the data. Use necessary code to read the description of the dataset, which
contains 65 samples and 11 variables.
# Install the package if you never did
install . packages (” UsingR “)
# Load the pacakge
library ( UsingR )
# Load the UScereal dataset
data (” UScereal “)
Problem 1 (1 × 3 = 3 points)
Let’s first clean the data:
(a) Replace the levels of the factor variable mfr to their full names, i.e. “G” for General
Mills, “K” for Kelloggs, “N” for Nabisco, “P” for Post, “Q” for Quaker Oats, and “R” for
Ralston Purina. (Hint: use the function levels())
(b) Turn the variable shelf to a factor variable, of which levels are “1” for low, “2” for
middle, and “3” for upper
(c) Create a new variable named Product for the product name. (Hint: use the function
rownames()) to access the name for each sample
Hint: You should get the following response after applying the function str() on the
cleaned dataset
’data . frame ’: 65 obs . of 11 variables :
$ mfr : Factor w/ 6 levels ” General Mills ” ,..: 3 2 2 1
2 1 6 4 5 1 …
1
$ calories : num 212 212 100 147 110 …
$ protein : num 12.12 12.12 8 2.67 2 …
$ fat : num 3.03 3.03 0 2.67 0 …
$ sodium : num 394 788 280 240 125 …
$ fibre : num 30.3 27.3 28 2 1 …
$ carbo : num 15.2 21.2 16 14 11 …
$ sugars : num 18.2 15.2 0 13.3 14 …
$ shelf : Factor w / 3 levels ” Lower “,” Middle ” ,..: 3 3 3
1 2 3 1 3 2 1 …
$ potassium : num 848.5 969.7 660 93.3 30 …
$ vitamins : Factor w/ 3 levels “100%”,” enriched ” ,..: 2 2 2
2 2 2 2 2 2 2 …
$ product : chr “100% Bran ” “All – Bran ” “All – Bran with
Extra Fiber ” ” Apple Cinnamon Cheerios ” …
Problem 2 (1 × 7 = 7 points)
Let’s analyze the data. For each figure, please make it complete/readable, in other words,
it should include all the label information, title, and legend if necessary.
(a) Calculate the Pearson correlation coefficient between calories and each of the seven
nutrition facts, protein, fat, sodium, fibre, carbo, sugars, and potassium, and
show their numbers.
(b) Make a bar plot of the resulting correlations in (a) and arrange the nutrition facts in
decreasing order in terms of their correlation with the calories. Which nutrition fact
has the highest values?
(c) Make a scatter plot where y axis represents calories and x axis represents the nutrition fact with the largest Pearson correlation coefficient to calories in (b). Add a
trend line and interpret the meanings of intercept and slope in this context.
(d) The main cereal manufactures are General Mills and Kelloggs, since they have larger
numbers of samples than any others. Make density curves of calories to compare
these two manufactures in one plot and describe their shapes, respectively.
(e) Are calories significant different between these two main manufacturers, i.e. General Mills and Kelloggs? Answer this question via showing an appropriate plot.
(f) Make seven side-by-side box plots to compare each of the seven nutrition facts, including protein, fat, sodium, fibre, carbo, sugars, and potassium, among the six
manufactures. Discuss which manufacture aims for a better healthy diet?
(g) Make a stacked bar plot to show the relationship between manufacture (i.e. mfr) and
shelf placement (i.e. shelf). (Hint: use meaningful or your favorite colors to indicate
different manufactures, you may consider to use the color tones in their logos)
2 STAT 3355
3 STAT 3355