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Answer each with approximately  300-400  words  (each part A, B, C, D, E), depending on how much information is being requested

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Answer each with approximately  300-400  words  (each part A, B, C, D, E), depending on how much information is being requested.  The last question (F)  involves only creation of a table only and no discussion is needed. Please create a Word Table or paste in something from Excel. 

aa) Please write a couple of sentences reminding us of the job/career/firm/industry you discussed in your first reflective writing. (This will help us understand your examples.). Last week you wrote about data analyst at Amazon.

A) QUALITATIVE DATA:

(i) Start by defining what is meant by  qualitative data . Then, discuss 2-3 examples of qualitative variables that are relevant in the industry/career you have been discussing. You should fully flush out these examples--why might you be interested in them, how and when they would they be collected, etc. Explain the context in which you might use them. 

(ii)  Illustrate an understanding of  ordinal versus nominal , by offering 2-3 examples relevant to your job/firm that fall into each category. Be sure to fully communicate an understanding of these concepts. 

NOTE THAT THE THINGS YOU DISCUSS ABOVE DO NOT HAVE TO BE VARIABLES YOU ARE ACTUALLY COLLECTING...JUST ONES THAT YOU COULD BE COLLECTING. 

B) QUANTITATIVE DATA:

(i) Start by explaining what is meant by  quantitative data .  Then offer examples of  quantitative variables and data that are relevant in the industry/career you have been discussing and how these variables relate to decision-making. Explain why you might be interested in them, how and when you might collect them, etc. Explain the context in which you might use them. 

(ii) Explain what variables are  discrete versus continuous , being sure to communicate an understanding of these concepts. Be sure that you explain these statistics concepts before offering examples.

NOTE THAT THE THINGS YOU DISCUSS ABOVE DO NOT HAVE TO BE VARIABLES YOU ARE ACTUALLY COLLECTING...JUST ONES THAT YOU COULD BE COLLECTING. 

C) DUMMY AND CATEGORICAL VARIABLES

(i) Explain the idea of a  dummy variable  (the simple kind with 2 states of the world). Come up with 3-4 examples of dummy variables that would be of interest to  your firm. Explain why you might be interested and when/how you might collect and use this information. (Try to not overlap examples that you have already discussed above.)

(ii) Explain the idea of a  categorical dummy variable . Come up a relevant examples of variables for which you would use a categorical dummy variable approach and discuss this fully. Explain why you might be interested in this information and when/how you might collect and use this information. (Try to not overlap examples that you have already discussed above.)

NOTE THAT THE THINGS YOU DISCUSS ABOVE DO NOT HAVE TO BE VARIABLES YOU ARE ACTUALLY COLLECTING...JUST ONES THAT YOU COULD BE COLLECTING. 

D) DATA SETS 1

(i) Explain the idea of a  cross-sectional data set. Then, offer a detailed example (related to your job/firm) that you could generate from information available to you, or that might be of interest if it could be collected. Be sure you have shown an understanding of why your example is cross-sectional. 

(ii) Explain the idea of a  time-series data set. Then, offer a detailed example (related to your job/firm) that you could generate from information available to you, or that might be of interest if it could be collected. Be sure you have shown an understanding of why your example is time-series. 

E) DATA SETS 2

(i) Explain the idea of a  panel data set. Then, offer a detailed example (related to your job/firm) that you could generate from information available to you, or that might be of interest if it could be collected. Be sure you have shown an understanding of why your example is panel.

(ii) Explain the idea of a  pooled data set. Then, offer a detailed example (related to your job/firm) that you could generate from information available to you, or that might be of interest if it could be collected. Be sure you have shown an understanding of why your example is pooled.

F) CONSTRUCT A DATA SET (for this we are  only looking for a table of data)

·

· Select 10 restaurants you are familiar with. They must include at least one fancy, one family sit down, and one fast food. 

· See the list of variables that you must code for these restaurants. 

· Create a  single table with data that shows how you would code the following quantitative and qualitative variables (some of which will need to be dummy variables or categorical variables). This will be a  machine ready data set. 

· But you will keep the qualitative information to help us in grading. (For example, if we were coding people we will have a column of male/female but then also code the dummy variable with 0 or 1).

· Be sure you have a header with variable names (like was used in the lectures).  

Variables you will code/include: 

·

· Restaurant name (we are just keeping this for organization but do not technically need it to run statistics)

· # of miles from your house (approx. rounded to whole mile)

· If is within 5 miles of your house

· If you have visited this restaurant in the past month

· If is a chain (either regional or national--doesn't matter)

· Type of restaurant category it fits into (fancy dining, casual sit down, fast food)