O'Reilly on Data

DECEMBER 9, 2019

We develop an ordinary least squares (OLS) linear regression model of equity returns using Statsmodels, a Python statistical package, to illustrate these three error types. We use the diagnostic test results of our regression model to support the reasons why CIs should not be used in financial data analyses. and an error term ??

Statistics 31

Statistics Uncertainty Risk Marketing 31

Cloudera

FEBRUARY 8, 2024

The table format was Iceberg and the underlying file format was ORC (similar tests can be performed with Parquet but we chose ORC as most Hive customers use ORC). We ran the ANALYZE command to gather both table and column statistics on all the base tables.

Snapshot 91

Snapshot Metadata Cost-Benefit Data Warehouse 91

The Unofficial Google Data Science Blog

DECEMBER 4, 2019

With those stakes and the long forecast horizon, we do not rely on a single statistical model based on historical trends. For example, we may prefer one model to generate a range, but use a second scenario-based model to “stress test” the range. A single model may also not shed light on the uncertainty range we actually face.

Forecasting 115

Forecasting Data Science Statistics Uncertainty 115

Jen Stirrup

OCTOBER 21, 2019

For the leaders, the simplest option can simply be doing nothing, but let someone run around burning themselves out so that eventually it becomes a test of patience and stamina, rather than a test of what is right and wrong. Office for National Statistics (2015) Gender Pay Gap. The Business Case for Diversity.

Data-driven 49

Data-driven Marketing Testing Insurance 49

CIO Business Intelligence

JULY 24, 2024

In 2003, Oxford University professor Nick Bostrom asked what happens if you ask a smart AI to make as many paperclips as possible. It’s just math and statistics.” And to find out if the fine-tuning has worked, the LLM needs to be tested on a large number of questions, asking the same thing in many different ways.

Risk 130

Risk Insurance Modeling Manufacturing 130