SophiaPretty

(5)

$14/per page/Negotiable

About SophiaPretty

Levels Tought:
Elementary,Middle School,High School,College,University,PHD

Expertise:
Accounting,Algebra See all
Accounting,Algebra,Applied Sciences,Architecture and Design,Art & Design,Biology,Business & Finance,Calculus,Chemistry,Communications,Computer Science,Economics,Engineering,English,Environmental science,Essay writing Hide all
Teaching Since: Jul 2017
Last Sign in: 304 Weeks Ago, 2 Days Ago
Questions Answered: 15833
Tutorials Posted: 15827

Education

  • MBA,PHD, Juris Doctor
    Strayer,Devery,Harvard University
    Mar-1995 - Mar-2002

Experience

  • Manager Planning
    WalMart
    Mar-2001 - Feb-2009

Category > Computer Science Posted 18 Nov 2017 My Price 10.00

data scientist for Acme Shopping, a large shopping

Case: Acme Shopping (For R)

 

You are the data scientist for Acme Shopping, a large shopping mall that incorporates a balanced tenancy of different types of stores along with eating areas. To understand your customers better, you conduct a survey to study beliefs on shopping. You test those beliefs by asking shoppers the six questions listed below. Shoppers then answer using a 7-point Likert scale, from 1 (strongly disagree) to 7 (strongly agree). Your goal is to group the shoppers at Acme Shopping into different segments using Ward’s method. The questions are listed below:

 

V1. Shopping is fun

V2. Shopping is bad for your budget

V3. I combine shopping with eating out

V4. I try to get the best buys while shopping

V5. I don't care about shopping

V6. You can save a lot of money by comparing prices

 

You also collect other data, such as income and number of mall visits. Do not include the other data in your analysis.

 

See the associated dataset for the case, “DataScience_8_Case_Shopping.xls”. The screenshot below shows a portion of the data. This case closely follows the dog food example in the lecture.

 

Untitled.png

 

1. Prepare the data by selecting the subset of the spreadsheet that you need (eliminate any explanatory material in the spreadsheet that is not part of the data). Save the data in comma separated values (CSV) format using the filename “acmeshop”. Read the data into R using the read.csv command. Print out the data in R to ensure it was loaded in correctly. Present the answers in an Adobe PDF or Microsoft Word document, including screenshots of your work in R.

 

2. Compute the distances between points in the dataset by using the “dist” function. Use the Euclidean method. Next, ask R to compute the hierarchical clusters (hclust), based on the distance matrix you found in the previous step. Present the answers in an Adobe PDF or Microsoft Word document, including screenshots of your work in R.

 

3. Plot the results of the “hclust” operation into a Dendogram tree diagram. Add boxes around clusters you identified in the Dendogram. Present the answers in an Adobe PDF or Microsoft Word document, including screenshots of your work in R.

 

4. Commentary: Based on the six questions we asked, what types of segments would you expect to find?

Include research: What types of segments are typically found by market research such as this? (Hint: Google “shopping mall customer segments”)

 

http://www.emeraldinsight.com/doi/abs/10.1108/09590550710828245

Attachments:

Answers

SophiaPretty
(5)
Status NEW Posted 18 Nov 2017 09:11 AM My Price 10.00

-----------  ----------- H-----------ell-----------o S-----------ir/-----------Mad-----------am ----------- Th-----------ank----------- yo-----------u f-----------or -----------you-----------r i-----------nte-----------res-----------t a-----------nd -----------buy-----------ing----------- my----------- po-----------ste-----------d s-----------olu-----------tio-----------n. -----------Ple-----------ase----------- pi-----------ng -----------me -----------on -----------cha-----------t I----------- am----------- on-----------lin-----------e o-----------r i-----------nbo-----------x m-----------e a----------- me-----------ssa-----------ge -----------I w-----------ill----------- be----------- qu-----------ick-----------ly

Not Rated(0)