Data Science 101

JANUARY 15, 2020

Bias ( syatematic unfairness in data collection ) can be a potential problem in experiments and we need to take it into account while designing experiments. Reliability: It means measurements should have repeatable results. For eg: you measure the blood pressure of a person. Statistics Essential for Dummies by D.

Experimentation 96

Experimentation Statistics Measurement Testing 96

The Unofficial Google Data Science Blog

OCTOBER 12, 2017

1]" Statistics, as a discipline, was largely developed in a small data world. Data was expensive to gather, and therefore decisions to collect data were generally well-considered. As computing and storage have made data collection cheaper and easier, we now gather data without this underlying motivation.

Experimentation 61

Experimentation Testing Statistics Metrics 61

Occam's Razor

MARCH 23, 2010

Part of it is fueled by a vocal minority genuinely upset that 10 years on we are still not a statistically powered bunch doing complicated analysis that is shifting paradigms. Having two tools guarantees you are going to be data collection, data processing and data reconciliation organization. Usually for free.

Analytics 118

Analytics Consulting Metrics Experimentation 118

datapine

APRIL 16, 2019

By implementing the right reporting tools and understanding how to analyze as well as to measure your data accurately, you will be able to make the kind of data driven decisions that will drive your business forward. What Is Data Driven Decision Making? Quantitative data analysis focuses on numbers and statistics.

Data-driven 287

Data-driven Dashboards Visualization Cost-Benefit 287