Name:

PBHL-B300 Homework #2

1. People with diabetes must monitor and control their blood glucose level. The goal is to maintain "fasting plasma glucose" between about 90 and 130 milligrams per deciliter (mg/dL). Ten (10) diabetics enrolled in a diabetes control class. Their fasting plasma glucose levels at 5 months after the end of the class are shown below:

141 158 112 153 134 95 96 78 148 172

Manually (show your work) calculate the mean, median, variance, and standard deviation of this sample of 10 diabetic glucose levels.

1. C-reactive protein (CRP) can be measured in the blood. Values increase substantially within 6 hours of an infection and reach a peak within 24 to 48 hours after. In adults, chronically high values have been linked to an increased risk of cardiovascular disease. In a study of apparently healthy children aged 6 to 60 months in Papua New Guinea, CRP was measured in 90 children. The units are milligrams per liter (mg/l). Here are the data from a random sample of 40 of these children.

0.00 3.90 5.64 8.22 0.00 5.62 3.92 6.81 30.61 0.00

73.20 0.00 46.70 0.00 0.00 26.41 22.82 0.00 0.00 3.49

0.00 0.00 4.81 9.37 5.36 0.00 5.66 0.00 59.76 12.38

15.74 0.00 0.00 0.00 0.00 9.37 20.78 7.10 7.89 4.93

Enter these data into R (creating a variable named "crp") using the following command:

> crp= c(enter the 40 raw data values, all separated by commas)

1. Using R, find the Q1, median, Q3, and mean for the crp
2. Calculate the IQR
3. Using the Q1, Q3, and IQR, determine which of the 40 values are outliers
4. Make a boxplot using R
5. Using R, find the variance and standard deviation for the crp
6. Make a histogram using R
7. Refer to the histogram to describe the shape of the data distribution of crp. Is it unimodal, bimodal, multimodal, or uniform? Is it symmetric, right skewed or left skewed?

Note: For all R work, show both your R commands and results. For any plots/graphs, please use the Zoom button to expand your graph (as we saw in class) and then paste the zoomed version to your homework.

1. Follow the directions shown in the second R Lab, "Introduction to Data", on the OpenIntro.org website to load the CDC dataset:

> source("http://www.openintro.org/stat/data/cdc.R")

Using this CDC dataset in R, do the following:

1. Using R and its table() command, make a contingency table of "genhlth" (5 General Health categories) by smoke100 (whether the respondent has smoked 100 cigarettes in their life).
2. Using the above contingency table, calculate the proportions of those who have smoked for each of the 5 General Health categories.
3. As shown in the R Lab, create 2 separate subset data sets for the males and the females.
4. Use the above subset data sets to find and report the means and standard deviations of the age, height, weight, and desired weight separately for the males and females. Make a table (by hand) reporting these statistics for each group.
5. Make a scatterplot of (X) age versus (Y) weight for the males. Yes or no, do you see an association between these variables, or do they look independent?

Note: For all R work, show both your R commands and results. For the last plot/graph, please use the Zoom button to expand your graph and then paste the zoomed version to your homework.