Advice on advanced analysis for end term Project
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I have an end of term project for a class in Applied Data Analytics. I am a software engineer of 18 years and I have learned a lot so far using R with little problems.
This question is less technical but more about approach to a real world problem. I have a dataset of about 25 variables from a pretend Survey on flights. It has all of the standard variables: 5 on biometrics, 10 on the characteristics of the flight , then another 10 related to the customer (flights with airline, Reward Member).
So my question is, given this task in the real world, what are some advanced or more sophisticated types of analysis I should research to include in this project? Our team came up with all the basic business questions: Does gender effect satisfaction, Does Time of Day effect Satisfaction, Flight Delays, etc.... Then some of the combination of some simple variables.
Again, in the real world, what are intermediate and senior level "Data Scientists" adding to this type of presentation. I would like to take a crack at the harder more sophisticated items.
Thanks for any advice/guidance any could provide!!
data-mining dataset data-science-model data-analysis
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I have an end of term project for a class in Applied Data Analytics. I am a software engineer of 18 years and I have learned a lot so far using R with little problems.
This question is less technical but more about approach to a real world problem. I have a dataset of about 25 variables from a pretend Survey on flights. It has all of the standard variables: 5 on biometrics, 10 on the characteristics of the flight , then another 10 related to the customer (flights with airline, Reward Member).
So my question is, given this task in the real world, what are some advanced or more sophisticated types of analysis I should research to include in this project? Our team came up with all the basic business questions: Does gender effect satisfaction, Does Time of Day effect Satisfaction, Flight Delays, etc.... Then some of the combination of some simple variables.
Again, in the real world, what are intermediate and senior level "Data Scientists" adding to this type of presentation. I would like to take a crack at the harder more sophisticated items.
Thanks for any advice/guidance any could provide!!
data-mining dataset data-science-model data-analysis
New contributor
Ethan Hodys is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
add a comment |
$begingroup$
I have an end of term project for a class in Applied Data Analytics. I am a software engineer of 18 years and I have learned a lot so far using R with little problems.
This question is less technical but more about approach to a real world problem. I have a dataset of about 25 variables from a pretend Survey on flights. It has all of the standard variables: 5 on biometrics, 10 on the characteristics of the flight , then another 10 related to the customer (flights with airline, Reward Member).
So my question is, given this task in the real world, what are some advanced or more sophisticated types of analysis I should research to include in this project? Our team came up with all the basic business questions: Does gender effect satisfaction, Does Time of Day effect Satisfaction, Flight Delays, etc.... Then some of the combination of some simple variables.
Again, in the real world, what are intermediate and senior level "Data Scientists" adding to this type of presentation. I would like to take a crack at the harder more sophisticated items.
Thanks for any advice/guidance any could provide!!
data-mining dataset data-science-model data-analysis
New contributor
Ethan Hodys is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
I have an end of term project for a class in Applied Data Analytics. I am a software engineer of 18 years and I have learned a lot so far using R with little problems.
This question is less technical but more about approach to a real world problem. I have a dataset of about 25 variables from a pretend Survey on flights. It has all of the standard variables: 5 on biometrics, 10 on the characteristics of the flight , then another 10 related to the customer (flights with airline, Reward Member).
So my question is, given this task in the real world, what are some advanced or more sophisticated types of analysis I should research to include in this project? Our team came up with all the basic business questions: Does gender effect satisfaction, Does Time of Day effect Satisfaction, Flight Delays, etc.... Then some of the combination of some simple variables.
Again, in the real world, what are intermediate and senior level "Data Scientists" adding to this type of presentation. I would like to take a crack at the harder more sophisticated items.
Thanks for any advice/guidance any could provide!!
data-mining dataset data-science-model data-analysis
data-mining dataset data-science-model data-analysis
New contributor
Ethan Hodys is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
Ethan Hodys is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
Ethan Hodys is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
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