"Until someone fortifies the material value of high-quality data as a consistent source of revenue and growth potential then companies will intentionally omit it from balance sheets."
Prashanth Southekal, PhD's Discussions
Regression Analysis
Started this discussion. Last reply by Wayne G. Fischer, PhD Feb 26. 10 Replies 1 Like
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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Prashanth Southekal, PhD posted a blog postWhy is Data Missing from the Balance Sheet?
I have been asked many times is data a business asset?. Why is it that an intangible asset like data is not in the company’s balance sheet - a statement of the assets, liabilities, and capital of a business at a particular point in time? Technically, an intangible asset is a non-physical asset that has a multi-period useful life. Examples of intangible business assets are patents, copyrights, customer lists, trademarks, brand names, logo, and data. While data in the recent years has provided…See More
Prashanth Southekal, PhD's blog post was featuredWhy is Data Missing from the Balance Sheet?
I have been asked many times is data a business asset?. Why is it that an intangible asset like data is not in the company’s balance sheet - a statement of the assets, liabilities, and capital of a business at a particular point in time? Technically, an intangible asset is a non-physical asset that has a multi-period useful life. Examples of intangible business assets are patents, copyrights, customer lists, trademarks, brand names, logo, and data. While data in the recent years has provided…See More
Wayne G. Fischer, PhD replied to Prashanth Southekal, PhD's discussion Regression Analysis"(Multiple) Linear Regression does *not* require a linear relationship between the response and the predictor(s). "Linear" refers to the requirement that the model being considered is linear in the *parameters* to be estimated."
Ramkumar Mambakkam replied to Prashanth Southekal, PhD's discussion Regression Analysis"You could use a normal Linear Regression, as your dependent variable is continuous. The categorical variables, can be converted to dummy variables ( if there are not many unique ones ).
Depending on the Overfitting or underfitting, you can…"
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…"
Mithun Alva replied to Prashanth Southekal, PhD's discussion Regression Analysis"Sounds great Prashanth. Were you able to check for the above assumptions?"
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."
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…"
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."
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 ."
Prashanth Southekal, PhD replied to Prashanth Southekal, PhD's discussion Regression Analysis"Thanks for your help Vincent"
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."
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- 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".
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Prashanth Southekal, PhD's Blog
Why is Data Missing from the Balance Sheet?
Posted on May 15, 2018 at 5:00am 1 Comment 1 Like
I have been asked many times is data a business asset?. Why is it that an intangible asset like data is not in the company’s balance sheet - a statement of the assets, liabilities, and capital of a business at a particular point in time? Technically, an intangible asset is a non-physical asset that has a multi-period useful life. Examples of intangible business assets are patents, copyrights, customer lists, trademarks, brand names, logo, and data. While data in the recent years…
Continue Transforming Quantitative Data to Qualitative Data
Posted on January 29, 2018 at 9:00pm 4 Comments 3 Likes
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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