Occam's Razor

APRIL 8, 2013

Sometimes, we escape the clutches of this sub optimal existence and do pick good metrics or engage in simple A/B testing. Let's listen in as Alistair discusses the lean analytics model… The Lean Analytics Cycle is a simple, four-step process that shows you how to improve a part of your business. Testing out a new feature.

Metrics 156

Metrics KPI Analytics Key Performance Indicator 156

Occam's Razor

AUGUST 22, 2011

Key To Your Digital Success: Web Analytics Measurement Model. Web Data Quality: A 6 Step Process To Evolve Your Mental Model. The Awesome Power of Visualization 2 -> Death and Taxes 2007. Five Reasons And Awesome Testing Ideas. Lab Usability Testing: What, Why, How Much. Experimentation and Testing: A Primer.

KPI 124

KPI Metrics Measurement ROI 124

The Unofficial Google Data Science Blog

JUNE 30, 2016

A naïve way to solve this problem would be to compare the proportion of buyers between the exposed and unexposed groups, using a simple test for equality of means. The choice of space $cal F$ (sometimes called the model ) and loss function $L$ explicitly defines the estimation problem. the curse of dimensionality).

Statistics 44

Statistics Optimization Modeling Experimentation 44

Occam's Razor

SEPTEMBER 19, 2011

How do you get over the frustration of having done attribution modeling and realizing that it is not even remotely the solution to your challenge of using multiple media channels? Then they isolated regions of the country (by city, zip, state, dma pick your fave) into test and control regions. Good lord I love this stuff!

Measurement 119

Measurement Advertising Testing Marketing 119

The Unofficial Google Data Science Blog

APRIL 19, 2021

by LEE RICHARDSON & TAYLOR POSPISIL Calibrated models make probabilistic predictions that match real world probabilities. To explain, let’s borrow a quote from Nate Silver’s The Signal and the Noise : One of the most important tests of a forecast — I would argue that it is the single most important one — is called calibration.

Modeling 122

Modeling IT Metrics Testing 122

The Unofficial Google Data Science Blog

APRIL 23, 2024

Experiments, Parameters and Models At Youtube, the relationships between system parameters and metrics often seem simple — straight-line models sometimes fit our data well. That is true generally, not just in these experiments — spreading measurements out is generally better, if the straight-line model is a priori correct.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

The Unofficial Google Data Science Blog

JULY 22, 2020

Another reason to use ramp-up is to test if a website's infrastructure can handle deploying a new arm to all of its users. The website wants to make sure they have the infrastructure to handle the feature while testing if engagement increases enough to justify the infrastructure. We offer two examples where this may be the case.

Experimentation 95

Experimentation Statistics Testing Strategy 95

Edwin Chen

MARCH 13, 2011

This is a summary of Bell and Koren’s 2007 Scalable Collaborative Filtering with Jointly Derived Neighborhood Interpolation Weights paper. Another way of thinking about this is that we are simply building a regression model. I’m now (very slowly) trying to clean up my notes and put them online. Bob likes Kate Winslet).

Optimization 40

Optimization Modeling Cost-Benefit Measurement 40

Occam's Razor

OCTOBER 15, 2012

I spend 70% of my time in the US and for those discussions I'm primary looking at speed (connection above), mobile penetration (yes, 2007 was the year of mobile!), Think of it as attribution modeling. :). and mobile intent to purchase (I love this data).

Advertising 136

Advertising Marketing Strategy Insurance 136

DataRobot Blog

MARCH 9, 2022

With that said, recent advances in deep learning methods have allowed models to improve to a point that is quickly approaching human precision on this difficult task. The first step in developing any model is gathering a suitable source of training data, and sentiment analysis is no exception. Sentiment analysis models.

Machine Learning 52

Machine Learning Deep Learning Modeling Measurement 52

The Unofficial Google Data Science Blog

MAY 31, 2016

Similarly, we could test the effectiveness of a search ad compared to showing only organic search results. Structure of a geo experiment A typical geo experiment consists of two distinct time periods: pretest and test. After the test period finishes, the campaigns in the treatment group are reset to their original configurations.

Advertising 42

Advertising Testing Sales Statistics 42

BizAcuity

MAY 10, 2022

Amazon strategically went with the pricing model of ‘on-demand’, allowing developers to pay only as-per their computational needs. 2007: Amazon launches SimpleDB, a non-relational (NoSQL) database that allows businesses to cheaply process vast amounts of data with minimal effort. EC2 was a more evolved version of a Virtual Machine.

Data-driven 52

Data-driven IoT Unstructured Data Data Lake 52

The Unofficial Google Data Science Blog

JULY 18, 2023

Parametric measurements Thus far, we’ve been discussing non-parametric approaches to measuring reliability and validity, but in this section we’ll present an approach to get the same measurements from parametric models. Each item receives multiple labels, and each person labeling this data assesses multiple items.

Measurement 52

Measurement Metrics Uncertainty Slice and Dice 52

Occam's Razor

FEBRUARY 7, 2011

The best option is to hire a statistician with experience in data modeling and forecasting. Brian Krick: Best way to measure and communicate "available demand" from available channels (social, search, display) for forecast modeling. Post Testing: Visits 30k. Please see the advice above. the web is so insanely fluid, 2.

Analytics 94

Analytics Measurement Metrics Predictive Analytics 94

O'Reilly on Data

DECEMBER 9, 2019

Recall from my previous blog post that all financial models are at the mercy of the Trinity of Errors , namely: errors in model specifications, errors in model parameter estimates, and errors resulting from the failure of a model to adapt to structural changes in its environment. For example, if a stock has a beta of 1.4

Statistics 27

Statistics Uncertainty Risk Marketing 27

Domino Data Lab

SEPTEMBER 25, 2019

One of the most common ways of fitting time series models is to use either autoregressive (AR), moving average (MA) or both (ARMA). These models are well represented in R and are fairly easy to work with. AR models can be thought of as linear regressions of the current value of the time series against previous values.

Forecasting 87

Forecasting Modeling Statistics Optimization 87

datapine

DECEMBER 28, 2021

To make sure the reliability is high, there are various techniques to perform – the first of them being the control tests, which should have similar results when reproducing an experiment in similar conditions. In 2007, Colgate was ordered by the Advertising Standards Authority (ASA) of the U.K. 3) Misleading statistics in advertising.

Statistics 363

Statistics Advertising Visualization Data mining 363