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P-Value
The p-value is a fundamental statistical measure utilized extensively in hypothesis testing. This metric serves as a yardstick to gauge the likelihood of observing an effect that is equal to or greater than the measured metric delta, assuming that the null hypothesis is valid. In simpler terms, the p-value quantifies the probability that the apparent disparity between your test and control groups is the result of mere chance.
Significance assessment
When the p-value is less than a predetermined threshold (typically 0.05), it is considered as supporting evidence for the presence of a genuine effect. In essence, this suggests that the dissimilarity you've noted is statistically meaningful and is improbable to have emerged solely due to random variability.
Methodological considerations
The computation of the p-value is contingent on the number of degrees of freedom inherent in the experiment. In cases where there's an ample sample size, a two-sample z-test is usually employed. However, when dealing with smaller experiments with degrees of freedom below 100, Welch's t-test is more suitable. Regardless of the chosen method, the p-value hinges on the calculation of metric mean and variance derived from both the test and control groups.
In summation, the p-value is an indispensable tool that helps researchers and data analysts ascertain the credibility of their findings, enabling informed decisions based on the statistical significance of observed discrepancies.
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Dave Cummings
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Don Browning
SVP, Data & Platform Engineering
"Statsig has been a game changer for how we combine product development and A/B testing. It's made it a breeze to implement experiments with complex targeting logic and feel confident that we're getting back trusted results. It's the first commercially available A/B testing tool that feels like it was built by people who really get product experimentation."
Joel Witten
Head of Data
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Laura Spencer
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Evelina Achilli
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Erez Naveh
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John Lahr
Growth Product Manager
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Preethi Ramani
Chief Product Officer
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Berengere Pohr
Team Lead - Experimentation
"Statsig is a powerful tool for experimentation that helped us go from 0 to 1."
Brooks Taylor
Data Science Lead
"We've processed over a billion events in the past year and gained amazing insights about our users using Statsig's analytics."
Ahmed Muneeb
Co-founder & CTO
"Leveraging experimentation with Statsig helped us reach profitability for the first time in our 16-year history."
Zachary Zaranka
Director of Product
"Statsig enabled us to test our ideas rather than rely on guesswork. This unlocked new learnings and wins for the team."
David Sepulveda
Head of Data
"Brex's mission is to help businesses move fast. Statsig is now helping our engineers move fast. It has been a game changer to automate the manual lift typical to running experiments and has helped product teams ship the right features to their users quickly."
Karandeep Anand
President
"We only had so many analysts. Statsig provided the necessary tools to remove the bottleneck. I know that we are able to impact our key business metrics in a positive way with Statsig. We are definitely heading in the right direction with Statsig."
Partha Sarathi
Director of Engineering
"Statsig has enabled us to quickly understand the impact of the features we ship."
Shannon Priem
Lead PM
"I know that we are able to impact our key business metrics in a positive way with Statsig. We are definitely heading in the right direction with Statsig."
Partha Sarathi
Director of Engineering
"Working with the Statsig team feels like we're working with a team within our own company."
Jeff To
Engineering Manager
"[Statsig] enables shipping software 10x faster, each feature can be in production from day 0 and no big bang releases are needed."
Matteo Hertel
Founder
"We use Statsig's analytics to bring rigor to the decision-making process across every team at Wizehire."
Nick Carneiro
CTO
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Wendy Jiao
Staff Software Engineer
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Carlos Augusto Zorrilla
Product Analytics Lead
"We have around 25 dashboards that have been built in Statsig, with about a third being built by non-technical stakeholders."
Alessio Maffeis
Engineering Manager
"Statsig beats any other tool in the market. Experimentation serves as the gateway to gaining a deeper understanding of our customers."
Toney Wen
Co-founder & CTO
"We finally had a tool we could rely on, and which enabled us to gather data intelligently."
Michael Koch
Engineering Manager
"At Notion, we're continuously learning what our users value and want every team to run experiments to learn more. It's also critical to maintain speed as a habit. Statsig's experimentation platform enables both this speed and learning for us."
Mengying Li
Data Science Manager
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Rami Khalaf
Product Engineering Manager
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Omar Guenena
Engineering Manager
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Michael Sheldon
Head of Data
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Elaine Tiburske
Data Scientist
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Paul Frazee
CTO
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Jared Bauman
Engineering Manager - Core ML
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Laura Spencer
Technical Program Manager
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Duncan Wang
Manager - Data Analytics & Experimentation
"Engineers started to realize: I can measure the magnitude of change in user behavior that happened because of something I did!"
Todd Rudak
Director, Data Science & Product Analytics
"For every feature we launch, Statsig saves us about 3-5 days of extra work."
Rafael Blay
Data Scientist
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Paulo Mann
Senior Product Manager