Publication Library
Ten Simple Rules for Initial Data Analysis
Description: Ten Simple Rules for Initial Data Analysis
Created At: 14 December 2024
Updated At: 14 December 2024
Mining of Massive Datasets
Description: Mining of Massive Datasets
Created At: 14 December 2024
Updated At: 14 December 2024
Experiments vs Computer Simulations - A Tale of Two Methods
Description: Experiments vs Computer Simulations - A Tale of Two Methods
Created At: 14 December 2024
Updated At: 14 December 2024
Randomness and Coincidences - Reconciling Intuition and Probability Theory
Description: We argue that the apparent inconsistency between people's intuitions about chance and the normative predictions of probability theory, as expressed in judgments about randomness and coincidences, can be resolved by focussing on the evidence observations provide about the processes that generated them rather than their likelihood. This argument is supported by probabilistic modeling of sequence and number production, together with two experiments that examine judgments about coincidences.
Created At: 14 December 2024
Updated At: 14 December 2024
Quantifying Decision Making for Data Science - From Data Acquisition to Modeling
Description: Organizations, irrespective of their size and type, are increasingly becoming data-driven or aspire to become data-driven. There is a rush to quantify value of their owninternal data or the value of integrating their internal data with external data, and performing modeling on such data. A question that analytics teams often grapple with is whether to acquire more data or expend additional effort on more complex modeling, or both. If these decisions can be quantified apriori, it can be used to guide budget and investment decisions. To that end, we quantify the Net Present Value (NPV) of the tasks of additional data acquisition or more complex modeling, which are critical to the data science process. We develop a framework, NPVModel, for a comparative analysis of various external data acquisition and in-house model development scenarios using NPVs of costs and returns as a measure of feasibility. We then demonstrate the effectiveness of NPVModel in prescribing strategies for various scenarios. Our framework not only acts as a suggestion engine, but it also provides valuable insights into budgeting and roadmap planning for Big Data ventures.
Created At: 14 December 2024
Updated At: 14 December 2024