(5/5)

should be done in RStudio. I have attached textbook. The code should be same as in the textbook.

STA 570 Take-Home Midterm 2

Instructions

• Try not to panic; you’ve got this!

• If you have any questions, please ask me.

• You may use our textbook, any resources I’ve provided to you in Bb Learn, and your notes from class or

office hours when completing this exam. You may not use other resources, especially not other people.

Any violation of this, no matter how minor, will result in a score of 0 for this part of the exam and

possibly further action.

• All work should be done in R/RStudio, and you should submit both your PDF and RMD to Bb Learn.

• This exam is due by 11:59 pm on December 4. To respect everyone’s schedule, late submissions—even

by 1 minute—may not be accepted. I recommend you treat 10 pm as the time its due, with 11:59 pm

being an extension to account for technological or other issues.

Problem

data()

?chickwts

A study conducted in the mid-1900s sought to investigate the effect of feed type on chick weight. Newly

hatched chicks were randomly allocated into six groups, and each group was given a different feed supplement.

Their weights in grams after six weeks are given along with feed types.

a.

Make a new data frame called chickwts2 in which the feed types are recategorized, using the fct_collapse

function (https://bookdown.org/dereksonderegger/444/factors.html), as animal-based (meatmeal and casein),

seed-based (sunflower and linseed), and bean-based (soybean and horsebean), naming the new factor levels

whatever you please. Then, reorder the factor levels using the fct_relevel function so that seed-based is

level 1, bean-based is level 2, and animal-based is level 3. Consider this data when completing this exam.

b.

What type of hypothesis test is appropriate for this type of data? Justify your choice.

c.

State the null and alternative hypotheses for this test, both symbolically (be sure to define the parameters of

interest) and in words in the context of the problem.

d.

Two common assumptions in statistical inference procedures are the independence of the measurements and

the sample’s representation of the population of interest. Neither of these assumptions are addressed in the

data description above. What’s a single question you could ask the primary investigator of this study to

assess the validity of these assumptions?

e.

Are there any other assumptions for your chosen hypothesis test? If so, state them.

f.

Create a visualization of the data. Without fitting a model or conducting the main hypothesis test, do any of

your assumptions from Part e appear to be violated? Either way, use appropriate sub-hypothesis tests to

corraborate or contradict your observations, stating which they do.

g.

Whether or not the assumptions from Part e were validated in Part f, conduct the main hypothesis test.

h.

Are there any assumptions that couldn’t be addressed until now? If so, state them.

i.

Validate the assumptions from Part h using first some visualizations and then some formal sub-hypothesis

tests. What is your final conclusion about the appropriateness of using this hypothesis test?

j.

Whether or not you concluded that this hypothesis test is appropriate, what is your statistical conclusion

regarding the null and alternative hypotheses at the 5% level of significance? Restate your conclusion in the

context of the problem.

k.

Does your conclusion above support the idea that animal-based feed is associated with higher average chick

weights relative to seed-based feed?

l.

If your answer to Part k was “yes,” justify your reasoning. If your answer to Part k was “no,” update your

analysis above to concisely answer this additional question, either by changing some options in your code or

by conducting an auxilliary hypothesis test (you needn’t check any additional assumptions for this exam,

although you would/should in your own research).

(5/5)

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