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Prashanth Southekal, PhD
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  • Calgary, AB
  • Canada
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Prashanth Southekal, PhD's Discussions

Regression Analysis

Started this discussion. Last reply by Sagar Dawda on Thursday. 8 Replies

I am doing some regression analysis. Some of the independent variables are continuous while some are categorical. The dependent variable is continuous. Can you please help me on which regression…Continue

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Tim Matteson liked Prashanth Southekal, PhD's discussion Regression Analysis
Thursday
Sagar Dawda replied to Prashanth Southekal, PhD's discussion Regression Analysis
"Hi Prashanth As an alternate approach you could try using a CART (Classification And Regression Tree) like Random Forest . This can be helpful especially in circumstances when the number of categories are more in your categorical feature. So…"
Thursday
Mithun Alva replied to Prashanth Southekal, PhD's discussion Regression Analysis
"Sounds great Prashanth. Were you able to check for the above assumptions?"
Thursday
Prashanth Southekal, PhD replied to Prashanth Southekal, PhD's discussion Regression Analysis
"Thanks Mithun for your help. Creating dummy variables as the key as I did not know that before. I was able to get this done and come up with a prediction model."
Thursday
Mithun Alva replied to Prashanth Southekal, PhD's discussion Regression Analysis
"Hi Prashanth. You can build a basic multiple regression model after creating dummy variables to represent the variables with the categorical values. Once you have built this base model, you will absolutely need to check for the following…"
Thursday
shaikh mohammed sabir replied to Prashanth Southekal, PhD's discussion Regression Analysis
"Read about ANCOVA model. You can handle categorical variable using dummy variable as said by Vincent above."
Thursday
Sayan Nandy replied to Prashanth Southekal, PhD's discussion Regression Analysis
"It's completely depend upon your objectives.As your dependent variable is continuous, I think you should use Multiple Linear regression Model ."
Thursday
Prashanth Southekal, PhD replied to Prashanth Southekal, PhD's discussion Regression Analysis
"Thanks for your help Vincent"
Thursday
Vincent Granville replied to Prashanth Southekal, PhD's discussion Regression Analysis
"You could turn your categorical variables into dummy binary variables (google "dummy variable"), and then use any standard regression. This is often done in the context of logistic regression."
Thursday
Prashanth Southekal, PhD's 2 discussions were featured
Wednesday
Prasanth liked Prashanth Southekal, PhD's blog post Transforming Quantitative Data to Qualitative Data
Feb 16
Wayne G. Fischer, PhD commented on Prashanth Southekal, PhD's blog post Transforming Quantitative Data to Qualitative Data
"Clarifications for completeness and accuracy (always a good thing when talking about data): o  The four types of data are nominal, ordinal, interval, and ratio. o  Depending on your business, all four may be commonly used. o…"
Feb 5
Nitin Pasumarthy commented on Prashanth Southekal, PhD's blog post Transforming Quantitative Data to Qualitative Data
"Thanks for the response. In order to feed as an input to a neural network.  Like one way to convert a categorical column is to use one hot encoding. What other techniques are commonly used?"
Feb 5
Prashanth Southekal, PhD commented on Prashanth Southekal, PhD's blog post Transforming Quantitative Data to Qualitative Data
"Hi Nitin, I have not come across any situation at work where I had to convert non numerical values to numerical values. I personally believe, changing the format and the values will affect data integrity.  But curious to know your use…"
Feb 5
John Faig liked Prashanth Southekal, PhD's blog post Transforming Quantitative Data to Qualitative Data
Feb 5
Nitin Pasumarthy commented on Prashanth Southekal, PhD's blog post Transforming Quantitative Data to Qualitative Data
"Is there a list of strategies to convert non numerical columns of a table to numerical values? For example, word2vec is a nice algorithm which assigns vectors to English words."
Feb 1

Profile Information

Short Bio
Prashanth Southekal brings over 20 years of Data and Information Management consulting/working for companies such as SAP AG, Shell, Apple, P&G, and General Electric. He has published two books on Information Management including the most recent "Data for Business Performance".
Field of Expertise
Analytics, Data Integration, Visualization, BI, Big Data, Data Science
Professional Status
Executive Management
Years of Experience:
20
Your Company:
DBP-Institute
Industry:
Consulting
Your Job Title:
Managing Principal
Interests:
Finding a new position, Networking, New venture, Recruiting, Other

Prashanth Southekal, PhD's Blog

Transforming Quantitative Data to Qualitative Data

Posted on January 29, 2018 at 9:00pm 4 Comments

The two main data types in business are nominal (categorical or qualitative data) and interval data (quantitative or continuous data). Nominal data are just categories on variables such as customer names, and marital status and you cannot do any mathematical operations on this type of data. Bar chart and Pie chart are usually used to describe nominal data. On the other hand, interval data hold numerical values on variables such as income, age, and invoice amount and you can do mathematical…

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