Data Analysis Assignment #2
Spring 2019
STAT 350
Your submitted document should include the following items. Points will be deducted if the
following are not included:
1. Type your Name, STAT 350 with your correct section number (e.g. STAT 350-xxx) and
Data Analysis Assignment #2 centered on the top of page 1 of your document.
2. Number your pages across your entire solutions document.
3. Your document should include the ANSWERS ONLY to the following FOUR questions
with each answer labeled by its corresponding number and subpart. Keep the questions in
order. Do NOT include the questions in your submitted document.
4. Generate all requested graphs and tables using JMP.
5. Upload your document onto Blackboard as a Word or pdf document using the link
provided by your instructor in Blackboard.
Elements of good technical writing:
Use complete and coherent sentences to answer the questions.
Graphs must be appropriately titled and should refer to the context of the question.
Graphical displays must include labels with units if appropriate for each axis.
Units should always be included when referring to numerical values.
When making a comparison you must use comparative language, such as “greater than”, “less
than”, or “about the same as.”
Ensure that all graphs and tables appear on one page and are not split across two pages.
Use α = 0.05 for all hypothesis tests throughout this assignment.
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Instructions
All questions will require you to load the data sets posted on the Blackboard course site.
1. Sea Slugs, common on the coast of southern California, live on a particular type of seaweed
known as vaucherian seaweed. The larvae from these sea slugs need to locate this type of
seaweed to survive. A study was done to try to determine whether chemicals that leach out of the
seaweed attract the larvae. Seawater was collected from an area with this type of seaweed at 5minute intervals as the tide was coming in and mixing with the chemicals. The idea was that as
more seawater came in, the concentration of the chemicals was reduced. Each sample of water
was then divided into 6 parts and larvae were introduced to each seawater part to see what
percentage successfully metamorphosed. Researchers wanted to know if there was a difference
in this percentage over the six time periods. The dataset SeaSlugs contains the results of the
investigation (Percent) for each of the six times (Time column in minutes). Dataset: SeaSlugs
1a) State the null and alternative hypotheses for this researcher in the context of the question.
1b) Enter the appropriate variables into JMP using Analyze → Fit Y by X using ‘Percent’ for Y
and ‘Time’ for X. Copy and paste the graphical display of the data into your document.
1c) Using the red triangle, select Unequal Variances to conduct Levene’s Test. Comment on
your findings and include the relevant output in your document.
1d) Again, using the red triangle, select Means/Anova to conduct an analysis of variance on the
data. Copy and paste the Analysis of Variance table into your document.
1e) Use your output from part 1d to make a decision concerning your hypotheses from part 1a.
Justify your decision at the = 0.05 level of significance.
1f) Now, using the red triangle, select Compare Means → Each Pair, Student’s t to determine
which times, if any, differ. Include the relevant output in your document.
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2. Iron-deficiency anemia is the most common form of malnutrition in developing countries,
affecting about 50% of children and women and 25% of men. Iron pots for cooking foods had
traditionally been used in many of these countries, but they have been largely replaced by
aluminum pots, which are cheaper and lighter. Some research has suggested that food cooked in
iron pots will contain more iron than food cooked in other type of pots.
One study designed to investigate this issue compared the iron content of some Ethiopian foods
cooked in aluminum, clay and iron pots. One of the foods was yesiga wet’, beef cut into small
pieces with several Ethiopian spices. The iron content of four samples of yesiga wet’ cooked in
each of the three types of pot is provided in the dataset, Iron1. Units are in mg of iron per 100
grams of cooked food.
2a) State the null and alternative hypotheses for the main effect in the context of the question.
2b) Use Analyze → Fit Y by X and copy and paste the graphical display of the data into your
document.
2c) Using the red triangle, select Unequal Variances to conduct Levene’s Test. Report on your
findings and include the relevant output in your document.
2d) Again, using the red triangle, select Means/Anova to conduct an analysis of variance on the
data. Copy and paste the Analysis of Variance table into your document.
2e) Use your output from part 2d to make a decision concerning your hypotheses from part 2a.
Justify your decision.
2f) Now, using the red triangle, select Compare Means → Each Pair, Student’s t to determine
which pot types, if any, differ. Include the relevant output in your document.
3. The researchers then expanded their study by examining the iron content of shiro wet’, a
legume-based mixture of chickpea flour and Ethiopian spiced pepper, and ye-atkilt allych’a, a
lightly spiced vegetable casserole. In the dataset, Iron2, these three foods are labeled “meat”,
“legumes”, and “vegetables.” Four samples of each food were cooked in each type of pot. The
units are as in question #2.
3a) Create boxplots to display the results by using Graph → Graph Builder. Use Iron as the Y
variable, Pot Type as the X variable and Food Type as the “Group X” variable, then select the
boxplot icon at the top. Title your graph and copy it into your document.
3b) State the two null and alternative hypotheses for the main effects in the context of the
question.
3c) State the null and alternative hypothesis for the test for interaction in the context of the
question.
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3d) Select Analyze → Fit Model and enter Iron in the Y box. Now highlight both FoodType and
PotType before selecting Macros → Full Factorial. Now click Run. Copy and paste the
Analysis of Variance and Effect Tests tables into your document.
Make sure you
select both
FoodType and
PotType before
clicking macros
3e) Use your output from part 3d to make decisions concerning your hypotheses from part 3b-3c.
Justify your decisions.
3f) Use the red triangle and select Factor Profiling → Interaction Plots. Copy and paste the
plots into your document.
3g) Use the interaction plots and your results from part 3e to help the researchers make a
recommendation for the people in these developing countries.
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4. A student at a university in Australia noticed that ants often congregated on bits of sandwich
that were dropped on the ground. She wondered what kind of sandwiches ants preferred to eat, so
she set up an experiment. Among the factors she considered were the Filling of the sandwich
(vegemite, peanut butter, ham and pickle) and the type of Bread (rye, whole wheat, multigrain,
white) used. She prepared 4 sandwich pieces for each combination of Bread and Filling.
Randomizing the order, she left a piece of sandwich near an anthill for 5 minutes, then trapped
the ants with an inverted jar and counted how many were on the sandwich. After waiting for the
ants to settle down the process was repeated on the next sandwich. The data in SandwichAnts
are based on the counts she collected. Dataset: SandwichAnts
4a) State the two factors and their levels
Factor A: __________________ Levels _____________________________________
Factor B: __________________ Levels _____________________________________
4b) What is the observational unit? ____________________________________________
What is the response variable? ____________________________________________
4c) How many total treatment groups are there in the experiment? ___________________
4d) How many replications were conducted for each treatment group? ________________
4e) How many total observations were conducted? _______________________________
4f) State the two null and alternative hypotheses for the main effects in the context of the
question.
4g) State the null and alternative hypothesis for the test for interaction in the context of the
question.
4h) Select Analyze → Fit Model and enter Ants in the Y box. Now highlight both Bread and
Filling before selecting Macros → Full Factorial. Now click Run. Copy and paste the Analysis
of Variance and Effect Tests tables into your document.
4i) Use your output from part 4h to make decisions concerning your hypotheses from parts 4f-4g.
Justify your decisions.
4j) Use the red triangle and select Factor Profiling → Interaction Plots. Copy and paste the
plots into your document. Compare this plot to your decision concerning the interaction effect in
part 4i.
4k) Use the red triangle by the Filling factor and select LS Means Student’s t to conduct a
student’s t post hoc procedure on the filling main effect. Copy and paste only the Connecting
Letters report into your document.
4l) Use the results from parts 4i and 4j, and your Connecting Letters report from part 4k to help
the student make a conclusion from her study.
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