EXTENSIVE STEP -BY-STEP GUIDE FOR TEAM ASSIGNMENT 1
CODE, OUTPUT, EXPLANATION, INTERPRETATION & EXTRA TIPS
Note: Original assignment text available at the end.
, MADS MADLAD |2
Note from MADS MADLAD:
Thank you for buying my guide. I sincerely hope it helps you excel and learn
from this course. When I was writing these I sometimes struggled with this
program, but there were no summaries available.
This is why I decided to write something that is truly complete with a lot of
effort put into it. It helped me and my friends get good grades, but I also
always had you in mind, the future reader. When necessary, I always went the
extra mile to make this summary, more readable, organized and complete.
If you feel like it, leave me a review of how the course is going using this
summary, it will make my day to hear your opinion good or bad!
Check out my other extensive summaries for other MADS courses:
Available on:
Contact info:
If you need help or have an inquiry, contact me: https://www.georgedreemer.com
Connect with me on LinkedIn: https://www.linkedin.com/in/georgedreemer/
Donations:
By no means am I looking for fellow students to send me money! But if you feel like sending
me some ETH or BTC, you can do so here:
--> ETH: 0x123e086c6808459e7fC6Ac7F64a77dBA1dDe0149
--> BTC: bc1qgwzc82vph5v8rmzef4ywechjf85772n7m2e22g
, MADS MADLAD |3
wishes you g ood luck & persev erance.
Grades Testimony:
, MADS MADLAD |4
Before we start:
- Clean workspace (optional):
- Load all necessary external packages (using librarian package!):
- Load custom functions (KMO, Bartlett.sphere, a_bic, center_scale):
- Load Dataset & check out the first few rows, get summary and structure:
, MADS MADLAD |5
- Before starting, we also rename our questionnaire variables to more descriptive names
related to the content of the question:
Question 1: What are the factors that can be derived from the many lifestyle and sustainable
clothing perception variables?
- Reduce these two sets of variables into a smaller number of factors, using Factor Analysis.
- Make sure to use standardized variables
- Apply an orthogonal rotation (varimax)
- Include some insights on how the different age categories score on the obtained factors
- Save the factor scores for the rest of your assignment
First, we handle the lifestyle questions (columns 11 to 23 in fashion):
1. Standardize the variables for lifestyle (columns 11 to 23)
2. Before doing checks related to FA, we check if our lifestyle question variables are correlated:
3. Although we are told to use FA, we can check whether it is appropriate by running KMO and
Bartlett (note: the teacher provided the KMO and Bartlett function code):
a. KMO (range: 0 – 1): Our KMO is very close to 1, which is what we want.
CODE, OUTPUT, EXPLANATION, INTERPRETATION & EXTRA TIPS
Note: Original assignment text available at the end.
, MADS MADLAD |2
Note from MADS MADLAD:
Thank you for buying my guide. I sincerely hope it helps you excel and learn
from this course. When I was writing these I sometimes struggled with this
program, but there were no summaries available.
This is why I decided to write something that is truly complete with a lot of
effort put into it. It helped me and my friends get good grades, but I also
always had you in mind, the future reader. When necessary, I always went the
extra mile to make this summary, more readable, organized and complete.
If you feel like it, leave me a review of how the course is going using this
summary, it will make my day to hear your opinion good or bad!
Check out my other extensive summaries for other MADS courses:
Available on:
Contact info:
If you need help or have an inquiry, contact me: https://www.georgedreemer.com
Connect with me on LinkedIn: https://www.linkedin.com/in/georgedreemer/
Donations:
By no means am I looking for fellow students to send me money! But if you feel like sending
me some ETH or BTC, you can do so here:
--> ETH: 0x123e086c6808459e7fC6Ac7F64a77dBA1dDe0149
--> BTC: bc1qgwzc82vph5v8rmzef4ywechjf85772n7m2e22g
, MADS MADLAD |3
wishes you g ood luck & persev erance.
Grades Testimony:
, MADS MADLAD |4
Before we start:
- Clean workspace (optional):
- Load all necessary external packages (using librarian package!):
- Load custom functions (KMO, Bartlett.sphere, a_bic, center_scale):
- Load Dataset & check out the first few rows, get summary and structure:
, MADS MADLAD |5
- Before starting, we also rename our questionnaire variables to more descriptive names
related to the content of the question:
Question 1: What are the factors that can be derived from the many lifestyle and sustainable
clothing perception variables?
- Reduce these two sets of variables into a smaller number of factors, using Factor Analysis.
- Make sure to use standardized variables
- Apply an orthogonal rotation (varimax)
- Include some insights on how the different age categories score on the obtained factors
- Save the factor scores for the rest of your assignment
First, we handle the lifestyle questions (columns 11 to 23 in fashion):
1. Standardize the variables for lifestyle (columns 11 to 23)
2. Before doing checks related to FA, we check if our lifestyle question variables are correlated:
3. Although we are told to use FA, we can check whether it is appropriate by running KMO and
Bartlett (note: the teacher provided the KMO and Bartlett function code):
a. KMO (range: 0 – 1): Our KMO is very close to 1, which is what we want.
