BADS Survey Analysis
Text Analytics using R
Divya Gumbira
Introduction
Business Analytics & Decision Science
This Notebook contains the analysis of the survey responses for the below questions from the students of the course Business Analytics and Decision Science 2019-2020.
Q1: What are the most important skills you have learnt in this module and why do you believe they are so important?
Q2: What other business analytics topics, methods or software skills would you like to learn after completing this module?
The analysis aims to gather insights to answer the below questions.
• What were the most frequently reported important skills that have been acquired from this module?
• What are the most associated tokens with these most frequently reported important skills?
• What business analytics topics, methods or software skills are BADS students most wanting
to learn next?
• What are the most associated tokens with these most frequently reported skills?
Question 1
Q1: What are the most important skills you have learnt in this module and why do you believe they are so important?
Top 10 Frequently used Terms in the survey:
## x freq
## 1 data 21
## 2 r 21
## 3 skill 20
## 4 analysis 14
## 5 forecast 12
## 6 learn 11
## 7 lot 10
## 8 understand 10
## 9 future 9
## 10 analyze 8
Top 10 Frequently Associated Terms in the survey:
## x freq
## 1 data analysis 7
## 2 future career 5
## 3 time series 5
## 4 skill learnt 4
## 5 career r 3
## 6 data analyze 3
## 7 learnt module 3
## 8 analysis factor 2
## 9 analysis lot 2
## 10 analysis skill 2
Terms most associated with the words of key significance : r, forecast, data, programming
## # A tibble: 6 x 3
## # Groups: word1 [4]
## word1 word2 count
## <chr> <chr> <int>
## 1 data analysis 7
## 2 career r 3
## 3 data analyze 3
## 4 data set 2
## 5 forecast method 2
## 6 job r 2Network of Frequently Associated Terms with the words of key significance : r, forecast, data, programming
Analysis Questions:
• What were the most frequently reported important skills that have been acquired from this module?
• What are the most associated tokens with these most frequently reported important skills?
R progrmming was reported as the acquired skill from this course most of the students, followed by forecasting, time series forecasting and data analysis.
Key features associated with R include career and job. It can be seen that the students view this as an industry required skill for career prospects. The students have associated forecasting with practical real life scenarios and the terms like ‘finance’, ‘stock’ are associated with it. Data analysis, data visualizations are identified as skills gained through this course.
Question 2
Q2: What other business analytics topics, methods or software skills would you like to learn after completing this module?
Top 10 Frequently used Terms in the survey:
## x freq
## 1 python 33
## 2 learn 28
## 3 data 16
## 4 module 12
## 5 skill 12
## 6 r 11
## 7 analysis 10
## 8 busy 9
## 9 analytics 8
## 10 complete 8
Top 10 Frequently Associated Terms in the survey:
## x freq
## 1 learn python 8
## 2 complete module 7
## 3 busy analytics 4
## 4 data analysis 4
## 6 data mine 3
## 7 learn tableau 3
Terms most associated with the words of key significance : python, skill, data, learn
## # A tibble: 6 x 3
## # Groups: word1 [4]
## word1 word2 count
## <chr> <chr> <int>
## 1 learn python 8
## 2 data analysis 4
## 3 data mine 3
## 4 learn tableau 3
## 5 python learn 3
## 6 software skill 3Network of Frequently Associated Terms with the words of key significance : python, skill, data, learn
Analysis Questions:
• What business analytics topics, methods or software skills are BADS students most wanting
to learn next?
• What are the most associated tokens with these most frequently reported skills?
One of the most popular tool the students seek to learn is Python programming along with Tableau, SQL, Spark and Matlab. Data analysis and Data mining are few of the top skills that the students are looking to learn. The token ‘learn’ is associated with a variety of other tokens, few of which can be identified as skills such as machine learning, database, programming, statistics, analytics which the students seems to want to acquire.
Sentiment Analysis
Sentiment Radar
The high levels in the sentiments of positivity and trust indicate that the students are happy with the skills they have acquired through the course. There is positive anticipation in wanting to acquire new skills along with mild apprehension.