New York Investment Network


Recent Blog


Pitching Help Desk


Testimonials

"Our small, early-stage company recently signed up for your service. We got numerous inquiries, several of which we are pursuing, and hopefully will find an investor partner as a result. It is almost impossible for young companies to attract investment capital in the current financial climate, but you managed to bring a number of qualified and interested parties to the table. I would recommend your service to any early-stage company seeking capital. Bruce Jones, CFO "
Bruce Jones

 BLOG >> Recent

Bayesian Entrepreneurship [Bayesian Inference
Posted on April 18, 2013 @ 10:15:00 AM by Paul Meagher

A bit of housekeeping first. To keep track of my discussion of topics related to Bayesian Inference, I have created a blog category called "Bayesian Inference". You can click on the category link Bayesian Inference to see how my earlier blogs prepare the groundwork for my later blogs on Bayesian inference. If you are new to this topic, I recommend reading my oldest Bayesian inference blog first and then reading each one up to my most recent Bayesian inference blog. Later blogs build on earlier blogs.

To date I have focused on Bayesian Angel Investing and have offered up some ideas and code as to how Bayesian inference might be applied to angel investing. After introducing the idea of Bayesian Angel Investing I then offered a classification framework for Bayesian Angel Investing. This was followed by a blog on measuring classification accuracy. I then introduced some foundational concepts in Bayesian inference such as conditional probability, prior probability, Bayes Theorem, and the concept and calculation of likelihoods. My last blog discussed a Bayes Wizard application that computes conditional probabilities of startup success and failure according to Bayes Theorem. It was meant to tie some of these foundational concepts together into a simple and useful web application.

Bayes inference techniques are not limited to helping angel investors optimize their investment decision, they can also be used by entrepreneurs to optimize their startup decision making. For example, entrepreneurs must make decisions about how they should invest their startup capital in order to maximize their return on investment. Imagine that you are a new farmer and must make a decision about whether to invest in buying wheat seed for the upcoming growing season. To make an optimal decision here you might begin by estimating the joint probability of getting 28 cm or more of rain during the wheat growing season AND that your wheat yield will be 7800 kg/ha or more. You might estimate this value by tallying the number of instances of (rain >= 28 cm and wheat yield >= 7800 kg/ha) and dividing this by the total number of observations you have on rain amount and wheat yield. Lets assume the P(R>=28 cm & Y>=7800 kg/ha) = .18. From historical records you might also estimate that the probability of getting a rain amount >= 28 cm to be .21. Now using our definition of conditional probability P(H|E)=P(H&E)/P(E), we calculate P(Y>=7800 kg | R >= 28 cm) as follows:

P(Y>=7800 kg | R >= 28 cm) = P(R>=28 cm & Y>=7800 kg/ha) / P(R>=28cm) = .18/.21 = .86
This tells us that the probability of getting a good yield from our wheat is fairly high if we get 28 cm or more of rain during the wheat growing season. The probability of getting 28 cm of rain or more is, however, only .21 so we might want to examine other rainfall amounts and yield amounts to see if there is a good yield value for a more probable rain fall amount. This is how a startup farmer might go about making an optimal decision regarding whether to purchase wheat seed for the upcoming growing season. It might be noted that there is a very high correlation between rainfall amounts and wheat yield (correlation coefficient of .95) so of all the variables that a farmer might take into account in making a seed purchase decision, an investigation into rainfall amounts and wheat yields is a particularly important relationship to examine when projecting a probable return on investment. Don't waste your time calculating probabilities based upon factors that don't really matter that much.

There are two ways to make decisions - analytically or non-analytically. Making a decision analytically requires the quantification of the main elements in your decision problem so that you can compute answers. The main reason entrepreneurs might want to bother with analytic decision making is if they can make better decisions by adopting an analytical approach versus a non-analytical approach (perhaps "intuitive" would be a more favorable word to use). In some ways this dichotomy is false because most "analytic" decisions involve a combination of analytic and intuitive problem solving, however, it is worth emphasizing the distinction because the role of analysis in entrepreneurial decision making is not an aspect of entrepreneurship that is discussed much. It is worth examining whether Bayesian inference techniques might be useful for entrepreneurs to learn because they lead to more success. It is difficult to say whether this is true or not because the idea of Bayesian entrepreneurship has not been studied or promoted to date. Maybe this blog will help change this state of affairs by offering some instruction on how Bayesian inference techniques might be applied in entrepreneurial decision making.

Top ten wheat producers — 2011 (million metric ton)
People's Republic of China 117
India 86
Russia 56
United States 54
France 38
Canada 25
Pakistan 25
Australia 24
Germany 22
Kazakhstan 22
World total 469
Source: UN Food & Agriculture Organisation(FAO)

Permalink 

 Archive 
 

Archive


 October 2019 [1]
 September 2019 [1]
 July 2019 [1]
 June 2019 [2]
 May 2019 [2]
 April 2019 [5]
 March 2019 [4]
 February 2019 [3]
 January 2019 [3]
 December 2018 [4]
 November 2018 [2]
 September 2018 [2]
 August 2018 [1]
 July 2018 [1]
 June 2018 [1]
 May 2018 [5]
 April 2018 [4]
 March 2018 [2]
 February 2018 [4]
 January 2018 [4]
 December 2017 [2]
 November 2017 [6]
 October 2017 [6]
 September 2017 [6]
 August 2017 [2]
 July 2017 [2]
 June 2017 [5]
 May 2017 [7]
 April 2017 [6]
 March 2017 [8]
 February 2017 [7]
 January 2017 [9]
 December 2016 [7]
 November 2016 [7]
 October 2016 [5]
 September 2016 [5]
 August 2016 [4]
 July 2016 [6]
 June 2016 [5]
 May 2016 [10]
 April 2016 [12]
 March 2016 [10]
 February 2016 [11]
 January 2016 [12]
 December 2015 [6]
 November 2015 [8]
 October 2015 [12]
 September 2015 [10]
 August 2015 [14]
 July 2015 [9]
 June 2015 [9]
 May 2015 [10]
 April 2015 [10]
 March 2015 [9]
 February 2015 [8]
 January 2015 [5]
 December 2014 [11]
 November 2014 [10]
 October 2014 [10]
 September 2014 [8]
 August 2014 [7]
 July 2014 [6]
 June 2014 [7]
 May 2014 [6]
 April 2014 [3]
 March 2014 [8]
 February 2014 [6]
 January 2014 [5]
 December 2013 [5]
 November 2013 [3]
 October 2013 [4]
 September 2013 [11]
 August 2013 [4]
 July 2013 [8]
 June 2013 [10]
 May 2013 [14]
 April 2013 [12]
 March 2013 [11]
 February 2013 [19]
 January 2013 [20]
 December 2012 [5]
 November 2012 [1]
 October 2012 [3]
 September 2012 [1]
 August 2012 [1]
 July 2012 [1]
 June 2012 [2]


Categories


 Agriculture [71]
 Bayesian Inference [14]
 Books [15]
 Business Models [24]
 Causal Inference [2]
 Creativity [7]
 Decision Making [15]
 Decision Trees [8]
 Design [36]
 Eco-Green [4]
 Economics [12]
 Education [10]
 Energy [0]
 Entrepreneurship [59]
 Events [2]
 Farming [20]
 Finance [25]
 Future [15]
 Growth [18]
 Investing [24]
 Lean Startup [10]
 Leisure [5]
 Lens Model [9]
 Making [1]
 Management [9]
 Motivation [3]
 Nature [22]
 Patents & Trademarks [1]
 Permaculture [34]
 Psychology [1]
 Real Estate [2]
 Robots [1]
 Selling [11]
 Site News [15]
 Startups [12]
 Statistics [3]
 Systems Thinking [3]
 Trends [7]
 Useful Links [3]
 Valuation [1]
 Venture Capital [5]
 Video [2]
 Writing [2]