Western Michigan University h

Topic 1: How Words Affect Our Lives

Choose either question A or B to answer. Only one will be graded.

Question A:

In thinking about the importance of language, interview someone you know who has had a child (for instance, parent, grandparent, sibling, neighbor, yourself) and ask why they chose to name the child that name versus another name. What connotations did they associate with the names? What does this suggest about the importance of words?

Question B:

Think of labels that you use to identify yourself, such as personal traits (friendly, quiet, helpful, honest), social role (parent, friend, employee), physical descriptions (small, tall, strong, athletic, physically challenged). How do these labels influence your perspective and actions?

Topic 2: How Language Influences Political Campaign or Ad Campaign

Choose either Question A or B to answer. Only one will be graded.

Question A:

Study a present or past political campaign; and explain how language is used to present positive images of the candidates.

For example, when Secretary of State and past presidential candidate Hillary Clinton was first running for senator from the state of New York, her advisers struggled with how the campaign literature should present her, since voters knew her primarily as first lady to President Bill Clinton. Should the buttons and bumper stickers feature “Hillary Clinton,” “Hillary Rodham Clinton,” “Mrs. Clinton,” or “Hillary Rodham”? Each name might hold different connotations for voters concerning the candidate’s identity. Finally, the campaign managers decided to go with a more general and vague approach; her name became, simply, “Hillary.”

Question B:

An article in the business magazine Investment Vision advised readers to consider investing in products with ad campaigns that created powerful positive images. The article reminded readers that corporations spend $129 billion yearly on ads and that the most effective are those with a clear concept. The best campaigns, it believes, focus on one or a few words associated with the product, such as thrive for Kaiser hospitals, dependable for Maytag, or the classic We try harder for Avis rental cars (which led the company from a $3.2 million loss to a $1.2 million gain in the 1960s).

Assuming that companies desire positive connotations for their products, study the ad campaigns of several companies.

a. Discuss each company image and how it is achieved through the ads, focusing especially on the words that were chosen to represent the product or service.

b. Decide which campaigns are successful at creating strong, positive connotations. Support your conclusions with reasons.

Order this or a similar paper and get 20 % discount. Use coupon: GET20


Posted in Uncategorized

Western Michigan University H

Problem 1. A permutation test for a difference of medians (instead of a difference of means) can be performed using twoSamplePermutationTestLocation() in package EnvStats by including the following argument: fcn=”median”.

After using library(EnvStats) and attach(mtcars), use twoSamplePermutationTestLocation() with arguments of fcn =”median” and seed = 1 to perform a permutation test for the difference of medians between the 2 data vectors wt[vs == 0] and wt[vs==1].

–“seed = 1” replaces set.seed(1) for this function

twoSamplePermutationTestLocation(wt[vs == 0], wt[vs==1], fcn =”median”, seed = 1 )

What is the p-value of the test with seed = 1?

–The seed value must be included as an argument

(Answer in 0e-00 format)

Problem 2. The bootstrap can be applied equally easily to test the difference of medians, a difference of standard deviations, a difference of quantiles, etc.

–Unlike KS-test for the difference in CDFs, must specify a statistic to calculate a bootstrapped difference

  • Is the bootstrapped difference of standard deviations (sd’s) for wt significantly different from 0 (at p < 0.05) for cars with am = 0 (data vector x) and cars with am = 1 in mtcars (data vector y)? What is the bootstrapped 95% upper confidence limit for the difference in sd’s for wt between x and y using the “Basic” bootstrap?

–Remember to use set.seed(1)

(Answer up to 3 decimal places)

Problem 3. Use kruskal.test() to test whether mothers with different numbers of physician visits in first trimester (“ftv”) have the same median age, in the birthwt dataset in the MASS package



–Use kruskal.test()

What is the p-value for the test?

(Answer up to 5 decimal places)

Problem 4. Chi-squared tests (c2 tests) let us compare categorical data to the predictions from a model (goodness-of-fit test), or to compare finite distributions to each other to see whether they are the same (homogeneity test) and whether they are independent (independence test).



# Create contingency table for smoking vs. exercise levels

tbl = table(survey$Smoke, survey$Exer)

# Perform a chi-square test for independence to test whether Smoke and Exer are independent. What is the p-value of the test? (Answer up to 4 decimal places)

Interpretation: Can we reject the null hypothesis that Smoke and Exer are independent at a 5% significance level?

Order this or a similar paper and get 20 % discount. Use coupon: GET20


Posted in Uncategorized

Western Michigan University H

Problem 1.  Use plot(density()) to examine the smooth estimated density function (PDF) for variable hp (horsepower) in data frame mtcars.

–Use attach(mtcars) so you can refer to hp

How many peaks (0, 1, 2, 3, or more) does the estimated PDF for hp have?

(Answer in the numerical form e.g., 4)

Group of answer choices


Question 2

Problem 2. Create a stem-and-leaf diagram for variable mpg in data frame mtcars, and use it to answer the following question:

How many stems (rows) are there?  

How many cars belong to the second stem?  

–Example:  for stem(eruptions), there are 18 stems (rows). 

–5 eruptions belong to the 5th stem:  24 | 00228

–The corresponding data values are: 2.400 2.400 2.417 2.417 2.483

Can view these values using sort(eruptions)

Question 3

Problem 3. Fit a normal distribution to the variable hp in mtcars (i.e., estimate the parameters of the normal distribution by MLE).

–Use fitdist() in package fitdistrplus

What is the estimated standard deviation of the best-fitting (MLE) normal distribution?

–For mpg, it was sd* = 5.93203

(Answer up to 5 decimal places)

Question 4

Problem 4. Fit an exponential distribution to mtcars$hp by MLE using fitdist() in package fitdistrplus.

–First, use attach(mtcars) or data(mtcars) 

–Then use library(fitdistrplus)

  • First install fitdistrplus package with install.packages(“fitdistrplus”)

–Use the fitdist() function, with “exp” (with the quotes) as an argument, to tell fitdistrplus to fit an exponential distribution

–Name the result so you can plot it with denscomp()

Plot fitted distribution using denscomp()

The exponential distribution has a single parameter (“rate”).  What is the MLE estimate of rate for variable hp?

–Use print(fit_name) to see, where fit_name is whatever you named your fitsdist() result

–Ignore the standard error

(Answer up to 4 decimal places)

Question 5

Problem 5. Use kstest() to decide whether the null hypothesis that variable hp in the mtcars data frame has an exponential distribution can be rejected with 95% confidence. 

–Remember to attach(mtcars)

–Remember to use set.seed(1)

–Then use ks.test(hp, rexp(100, rate = )) as a template for your test of whether hp and the best-fitting exponential distributions have significantly different CDFs

–Plug the MLE value for rate (from your previous results from fitdist() for hp) into the above template

  • What is the p-value for this hypothesis test?
  • What should we conclude? 

(Please input the p-value in the answer tab up to 5 decimal places)

Question 6

Problem 6. Use shapiro.test() to decide whether we can reject with 95% confidence (a = 5% significance level) the null hypothesis that variable hp in the mtcars data frame has a normal distribution.

  • What is the p-value for this hypothesis test?

–For mpg, it is 0.1229.  What is it for hp? 

–Remember that we reject a null hypothesis at significance level a (confidence level 1- a) if the p-value (tail area) of the test < a.

(Answer up to 4 decimal places)

Question 7

Problem 7.  Using plot(density()), do you think the Age variable in the survey data set in package MASS is left-skewed, right-skewed, or neither?

(Please input left-skewed, right-skewed, or neither in the answer tab)

Question 8

Problem 8. Using boxplot(), how many outliers do you see for variable Pulse in the survey data set in package MASS?

–Remember to load MASS using library(MASS) before using attach(survey) or survey$Pulse

Order this or a similar paper and get 20 % discount. Use coupon: GET20


Posted in Uncategorized

Western Michigan University H

You are a Chief Information Officer (CIO) or Chief Medical Information Officer (CMIO), or similar position, of your healthcare system/provider firm (ABC).

Your CEO sent you the following two links to articles written by Stacey and Khuntia (2020):

Both articles highlight a point: “embrace digital healthcare”, but do not provide any further details on how to do it. Therefore, the CEO asked you to plan for it and write a memo to him. He wants specific justified recommendations and actionable plans to reorient the digital health strategy of ABC firm, and achieve success in the post-COVID-19 situation.

Your memo should be around two-three single-spaced pages, and will not exceed five pages. You may use the appendix for additional illustrations/materials. Your memo will consist of at least the following points.

  1. Define and describe the ABC firm briefly. Clearly articulate the healthcare service the firm is providing and the target customers. You may select your existing organization or any other. ABC firm can be a hospital, clinic, health system, or any provider-specific organization. Avoid pure-payor or finance-relevant firms. (10 points).
  2. Provide a brief narrative of the current health IT in ABC firm (10 points). You may provide good and bad aspects, success, and failures around current health IT in ABC firm.
  3. Recommendations and Action Plans
    • Recommendations with brief justifications for ABC firm to “embrace digital healthcare” (30 points): Remember, you make the case and then argue to win it. In any case, the future of the ABC firm is in your hands. You may limit the recommendation, and subsequent action plans to one area, such as providing quality care, patient satisfaction/empowerment, analytics, smart health, population orientation, etc.
    • Your action plan for ABC firm to “embrace digital healthcare” (30 points): Be optimistic but also practical. Mention what can be executed, and what cannot be, if any.
  4. Provide the relevance/contribution of your solution to the health care value propositions (20 points)
    • You will touch base on how the firm is positioned concerning the cost, efficiency, and effective delivery challenges in healthcare. How your proposed solution will link or provide any relevant context for the firm to address any or all of the above healthcare challenges (e.g., cost, efficiency, and effectiveness)?

You may use diagrams, illustrations, notes, bullet points to present your ideas. Remember, you will use the first-person perspective to write the memo to the CEO, in professional and business language. The CEO knows that you can collect academic and business references from the cases and papers discussed in the class to provide a highly articulated write-up. Your CEO is also well informed and reads academic and business papers to gather information. Thus, you are writing to an informed decision-maker or reader

Order this or a similar paper and get 20 % discount. Use coupon: GET20


Posted in Uncategorized