article thumbnail

The trinity of errors in applying confidence intervals: An exploration using Statsmodels

O'Reilly on Data

Because of this trifecta of errors, we need dynamic models that quantify the uncertainty inherent in our financial estimates and predictions. Practitioners in all social sciences, especially financial economics, use confidence intervals to quantify the uncertainty in their estimates and predictions.

article thumbnail

Transforming FSI in ASEAN with Cloud Analytics

CIO Business Intelligence

auxmoney began as a peer-to-peer lender in 2007, with the mission of improving access to credit and promoting financial inclusion. Much of this reluctance stems from the regulatory environment, arising from lengthy reviews and approvals processes, or even simple near-term regulatory uncertainty. .

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

The Lean Analytics Cycle: Metrics > Hypothesis > Experiment > Act

Occam's Razor

Circle of Friends was a social community built atop Facebook that launched in 2007. They might deal with uncertainty, but they're not random. They celebrated a bit, then went on to fix the next biggest problem in the business. Case Study 2: Circle of Friends.

Metrics 157
article thumbnail

Why model calibration matters and how to achieve it

The Unofficial Google Data Science Blog

bar{pi} (1 - bar{pi})$: This is the irreducible loss due to uncertainty. If calibration matters, our recommendation is to follow the paradigm proposed by Gneiting (2007) : pick the best performing model amongst models that are approximately calibrated, where "approximately calibrated" is discussed in the next section.

Modeling 122
article thumbnail

Towards optimal experimentation in online systems

The Unofficial Google Data Science Blog

Crucially, it takes into account the uncertainty inherent in our experiments. There is also uncertainty related to our modeling choices — did we select the correct polynomial embedding function $f(x)$, or is the true relationship better described by a different polynomial embedding?

article thumbnail

Changing assignment weights with time-based confounders

The Unofficial Google Data Science Blog

For this reason we don’t report uncertainty measures or statistical significance in the results of the simulation. From a Bayesian perspective, one can combine joint posterior samples for $E[Y_i | T_i=t, E_i=j]$ and $P(E_i=j)$, which provides a measure of uncertainty around the estimate. 2] Scott, Steven L. 2015): 37-45. [3]

article thumbnail

New Thinking, Old Thinking and a Fairytale

Peter James Thomas

King was a wise King, but now he was gripped with uncertainty. – Gartner 2007. “60-70% The Wizard declared his determination to deploy his discerning divination daily [11] , should the King confer on him the high office of Chief Wizard of Suzerain [12]. The office of Chief Wizard commanded a stipend that was not inconsiderable.