Hello,I’ve attached bellow a file with an exercise document which is pretty simple and straight forward. Please let me know if anything else is needed.Thank you so much in advance!Instructions: Please type your answers to the following questions in complete sentence answers format
with explanations, to this file, if possible. (Use this doc file and submit your final answers by adding your
work to this file – submit a doc/docx file).
1. The California Air Resources Board’s air quality monitoring program collects accurate real-time
measurements of ambient level pollutants at 40 monitoring sites located throughout the state. One typical
measurement used to assess air quality is the concentration of particulate matters less or equal than 2.5
μm in diameter (PM2.5). High levels of PM2.5 can cause serious health and respiratory problems. Daily
measurements of PM2.5 at the monitoring sites are collected at 3 random times during the day. Answer
the following questions:
a. Identify the variable and the unit of measurement. Is the variable quantitative or qualitative?
What is the implied population?
b. Is the variable random? What factors can contribute to the random nature of the variable in
question? In other words, what are some sources of variability and uncertainty in the variable? What
sources of variability in the random variable does the sampling scheme described above capture?
c. Describe one source of variability that the above sampling is not capturing. How would you design
this observational study to capture this source of variability?
d. What is described here is an observational study. How would you design a controlled experiment
to study the impact of PM2.5 to describe potential health problems arising from PM2.5? Describe some
challenges with designing such an experiment.
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2. You want to evaluate the effect of fertilizer treatment on tomato plant growth.
a. Describe how would you conduct an experiment using a completely randomized design in order to
evaluate if the fertilizer increases the growth of the tomato plants. Is there a control and a
treatment in this experiment? A placebo effect? Are there any lurking variables in this experiment?
b.
What other factors may impact the growth of tomato plants? Mention one factor you can control
in an experiment, and one that you cannot. How would you change your design for this
experiment, if you wanted to consider the impact of an additional factor?
3. Conduct your own observational study. Consider the population to be “students at USF”. You are
interested in studying students’ study time and free time, in number of hours a week. Explain what
sampling strategy you would use and justify why your strategy is representative of “students at USF”? If it
is not, which population is your sample representative of? Report any sources of bias, and comment on
how you would improve your observational study.
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4. The following graph summarizes data on days with reduced visibility in the city of Brisbane, Australia.
a. What type of graph is this? Discuss what the graph is showing in a small paragraph (3-4 sentences).
b. In 1986, several power stations were closed and backyard burning was banned. Based on the data,
does this appear to have affected visibility in Brisbane? Can we establish a cause-and-effect
relationship based on this graph? Explain why or why not.
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5. The following graphs are produced using data on the daily ozone levels over time in the city of London,
as well as data on daily deaths over the same period of time, as given in the following plots:
Source: Bhaskaran et al., 2013 Int J Epidemiol. 2013 Aug; 42(4): 1187–1195
a. Based on visual inspection of these graphs it appears that there may be a relation between the
daily deaths and the ozone levels. What graph would you use to investigate more effectively
whether there is a relationship between the two variables?
b.
The ozone levels data are affected by seasonality, and this is why they show a periodic, cyclic
behavior. Are the following statements true or false?
i. The general health condition of the people sampled may be a confounding variable, because it
also follows a periodic behavior with time.
ii. Temperature may be a confounding variable as it also follows a periodic behavior in time (wintersummer) and is known to affect mortality rates.
iii. There are no confounding factors. Ozone concentrations in the air are uniquely related to
mortality rates.
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6. Use the following graph of profit over time to answer the following questions.
a. What is the main take-home message from the graph? Write a discussion of the graph in a short
paragraph (3-4 sentences). Is the graph misleading in any way?
b. Enter the data you see in the above graph in Excel. Put Years in one column, and the corresponding
profits in another column. Then Insert-Chart-Column. Adjust your graph to use all important
components of a good graph (axes labels, appropriate axis scale etc.), and copy paste your graph
below. Comment on whether the take-home message is now different.
7. Dissolved oxygen data for two stations are provided for two monitoring stations in CA. Create the
following graphs, paying attention to axis labels, axis scales, and other important graph elements:
a. A graph showing how the maximum daily DO changed over time comparing the two
stations. Copy paste your graph here.
b. For your graph, write 2-3 sentences describing all important features of the graph. What
do we learn from the graph? Combine all your writing in one paragraph that gives the
overall description of dissolved oxygen concentrations in the two monitoring stations.
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