#data search results
Even with data and internet unavailability I will show up Answering this question to my best knowledge Remember we are just touching these s topics for the first time and we are still going to revisit it again. #data #statistics #public
This is day six of showing up and studying statistics And today we are touching measures of position If you have been learning or solving with me Comment or say hi #data #stats #buidinginpublic
Unpopular option: The hype around conversational BI is real, but the winning setups still rely on governed metrics and strong design so users don’t drown in options and confusion. What do you think? #powerbi #selfservice #data #analytics
2. We cannot always trust a sample to represent the population because of: Sample bias Sample anomalies These can affect the sample and make it not represent the whole population. #data #statistics #public
I failed some of them , using the questions can u recognise my wrong answer and help me correct them. Explaining your own thoughts See you next time , bye #data #statistics #public
1. We use a T-score here because not all the information is given. T-score is used when not all data is given, while Z-score is used when all data is given. 2. (Your attempt) The numerator represents how messy the data is. #data #statistics #public
3. Anomalies are rare and typically ≥ 3 standard deviations from the mean. Outliers are a larger group of points that look unusual but are not necessarily ≥ 3. 3. T-score intuition #data #statistics #public
Explanation: The Z-score is 2 standard deviations above the mean. It is close to the mean, not an extreme value. An extreme value (an anomaly) is usually around ±3 or more. 2. Outliers and anomalies 1. Z = 3.2 #data #statistics #public
#AI is only as good as the #data feeding it. bit.ly/4tLFu7v #ArtificialIntelligence #AIStrategy #BusinessLeadership #DigitalTransformation #AIAdoption #EnterpriseAI #FutureOfBusiness
This point is outside the ±3 (99.7%) band because it is greater than 3. So it is considered an anomaly. 2. Z = 1.8 This point is not inside the 95% band (±1.96). It is not unusual enough to be an anomaly. It is still relatively close to the mean. #data #statistics #public
if you work with data / ML / AI , are you in academia, research, or industry? or still in your learning phase? just curious 🤔 #AI #Data #Tech #DataScience
How generative #AI ‘persuasion bombs’ users — and how to fight back buff.ly/8A3FRqX @MITSloan @BCG #tech #data #business #digital #innovation #leadership #management #CIO #CTO #CDO #CEO #genAI #LLM #digitaltransformation #disruption #jobs #skills #futureofwork
📊 Extreme mispricing Will 2026 be the fourth-hottest year on record? Market: 5.0% AI: 84.0% Edge: +79.0% Market is massively underestimating this. Climate probabilities ≠ public sentiment. 👉 sorsnow.com/bet/96994 #Climate #Data #PredictionMarkets @Polymarket
🧠 Simple rule: If AI ≈ market → no edge If AI ≠ market → opportunity That’s it. 👉 sorsnow.com/alpha #Trading #Data #Alpha
Its been a few weeks since I last looked properly at my portfolio as life has been extremely hectic. But thankfully I'm back in positive YTD territory after a disappointing start to 2026. Biggest ⬆️ #DATA GlobalData: +5.8% #NIOX Niox: +1.5% #MMIT Mobius Inv Trust: +0.7% Biggest
Day 15/30📊 Today I cleaned and merged big data set Data cleaning is really time consuming. I almost gave up but I didn’t 🥲 #LearningInPublic #data #excel
#Analytics practitioners are very good at solving well-defined problems. But few are very good at analyzing, defining, & articulating the problems. "Problem formulation in analytics" ➡️msightanalytics.com/home/f/problem… #Data #Statistics #DataScience #MachineLearning #AdvancedAnalytics #AI
Use Synthetic #Data to Simulate Workforce Evolution Without Exposing Employee Data by @antgrasso #DataScience #BigData
What does the move to 2D #barcodes mean for grocery? GS1 US breaks down core scanning and processing requirements, readiness considerations, and how the added #data in 2D barcodes can enable new grocery use cases. Don’t miss the 5/12 GroceryTech session. bit.ly/48AkeK0
PAGINA - SUSPECT KYC WHOIS DATA IS SKETCH. MANIPULATED BY REGISTRARS WHO DON'T OWN THE ASSET. Reform. You can be first. ++//++ #DATA #SKETCHY #DOMAIN #MARKET #REFORM #DIGITAL #WAR #WTI #FUTURE #DIGITAL #ASSETS FAQ NOW: faqdomain.com COMING SOON:
I failed some of them , using the questions can u recognise my wrong answer and help me correct them. Explaining your own thoughts See you next time , bye #data #statistics #public
2. We cannot always trust a sample to represent the population because of: Sample bias Sample anomalies These can affect the sample and make it not represent the whole population. #data #statistics #public
4. Measures of position in context 1. A score that is 2.5 standard deviations above the mean is close to the mean. It is not an anomaly because anomalies are usually ≥ 3. It may not even be an outlier. #data #statistics #public
1. We use a T-score here because not all the information is given. T-score is used when not all data is given, while Z-score is used when all data is given. 2. (Your attempt) The numerator represents how messy the data is. #data #statistics #public
3. Anomalies are rare and typically ≥ 3 standard deviations from the mean. Outliers are a larger group of points that look unusual but are not necessarily ≥ 3. 3. T-score intuition #data #statistics #public
Out on the course spittin knowledge. How do you blend art with science? You got to understand how the data factors into real life. #golflife #golfswing #data #science #frenchbulldog
This point is outside the ±3 (99.7%) band because it is greater than 3. So it is considered an anomaly. 2. Z = 1.8 This point is not inside the 95% band (±1.96). It is not unusual enough to be an anomaly. It is still relatively close to the mean. #data #statistics #public
Explanation: The Z-score is 2 standard deviations above the mean. It is close to the mean, not an extreme value. An extreme value (an anomaly) is usually around ±3 or more. 2. Outliers and anomalies 1. Z = 3.2 #data #statistics #public
1. Z-score basics 1. Z = (80 − 70) ÷ 10 = 10 ÷ 10 = +1 Interpretation: The Z-score is 1 standard deviation above the mean. 2. Z = (55 − 70) ÷ 10 = −15 ÷ 10 = −1.5 The Z-score is below the mean. 3. Z = (130 − 100) ÷ 15 = 30 ÷ 15 = 2 #data #statistics #public
Even with data and internet unavailability I will show up Answering this question to my best knowledge Remember we are just touching these s topics for the first time and we are still going to revisit it again. #data #statistics #public
This is day six of showing up and studying statistics And today we are touching measures of position If you have been learning or solving with me Comment or say hi #data #stats #buidinginpublic
Your next opportunity might be closer than you think. Click to learn more about this open role in Chandler, AZ. bit.ly/3R3qnrX #data
para você resistir e responder de maneira estratégica e organizada ao poder das bigtechs, não repita o que os techbros disserem sobre si mesmos – e siga @ctrlz.org.br para ajudar a retomar a nossa Internet. #bigtech #data #sales #marketing
Fantastic discussion! 💡 As an industry we have “a lot of data & very little information…” #data #AI — Volkmar Uhlig @IBM Enter the Agentic workforce. Now agents can start asking real business questions, letting teams run ‘what if’ experiments at scale. #IBMThink @IBM
Wood Mackenzie introduces “physical intelligence” to track oil markets in real time, using sensors and satellites to detect disruptions before public data. The result: faster decisions and a major trading advantage. #OilMarket #Data drive.google.com/drive/u/1/fold…
Your next opportunity might be closer than you think. Click to learn more about this open role in Sydney, Australia. bit.ly/4tcxwnm #data
Laser ruler via @IntEngineering #tech #digital #data
Dashboards tell you what happened. #DecisionIntelligence tells you what to do next. In the latest from @NationalPestMgt, David Libesman breaks down why the future of #pestcontrol isn’t just more #data, it’s smarter, faster decisions powered by it: ow.ly/o5fe50YUHZq
Unpopular option: The hype around conversational BI is real, but the winning setups still rely on governed metrics and strong design so users don’t drown in options and confusion. What do you think? #powerbi #selfservice #data #analytics
if you work with data / ML / AI , are you in academia, research, or industry? or still in your learning phase? just curious 🤔 #AI #Data #Tech #DataScience
And how many people that actually SUCCESSFULLY automated something? 😅🤣 #powerbi #company #data #analytics #dataanalytics
Use Synthetic #Data to Simulate Workforce Evolution Without Exposing Employee Data by @antgrasso #DataScience #BigData
🚘 #Web3 should reward participation, not just attention. That is why $NTH is interesting. Users can contribute mobility #data, receive token rewards, and spend those rewards on #ecofriendly electric mobility charging. With #carboncredits built into the structure, this
On 12 July 2024 COPF presented its report to @ParliamentLK on the e-visa scam. In that report we found massive #data breaches and lack of data #protection. See Report at parliament.lk/uploads/comrep… 3.5 the issue that triggered termination of the contract. Our urgent recommendation
#AI is only as good as the #data feeding it. bit.ly/4tLFu7v #ArtificialIntelligence #AIStrategy #BusinessLeadership #DigitalTransformation #AIAdoption #EnterpriseAI #FutureOfBusiness
#AI Is Only As Good As The #Data It’s Fed. Read This To Understand Why Data Readiness Is Crucial To Capitalize On AI For Your Company => ds3-bandwidth.com/2025/06/01/to-… #ArtificialIntelligence #DataReadiness @antgrasso @TheHighway2AI @Khulood_Almani @YvesMulkers @HaroldSinnott @YuHelenYu
The public opposition to AI infrastructure is heating up tcrn.ch/4s3xSwq #datacenters #data #infrastructures
♻️ #EcoFriendly rentals are where the loop becomes real, not theoretical. $NTH makes that possible by converting mobility #data into #tokens. Without #reward and spendability, users are just donating value. That’s why #Web3 needs to change the default, and this is one way.
🌍 The 2025 Global Tree Cover Loss #Map update from @UMD_GLAD and @globalforests is out! Explore the latest tree cover loss #data: 🌲 Forest Loss: glad.earthengine.app/view/global-fo… 🔥 Forest Loss due to Fire: glad.earthengine.app/view/global-fo… #TreeCoverLoss #GlobalForestWatch @umdgeography
Intelligent Document Processing - 60% accuracy. DocCenter achieving 90%+. Usage doubling every quarter. 6 weeks time to value. #AppianWorld #Data
Scientists & Researchers Deaths, Disappearances & Suspicious Circumstances Database (1941–2026) 34 compiled cases. Many verified through news/official records. Thread below 👇 #Science #Research #Data
Stay informed and ahead of the curve with The Technicity Chronicle. We dive into the numbers and #data from diverse fields to show you what's truly shaping our world. #tech #business 📖 shorturl.at/HpwT4 @technicitymag @gvalan @DrFerdowsi @junjudapi @mary_gambara
#California Privacy Agency Invites Comments on CCPA Application to Employee and Applicant Data natlawreview.com/article/califo… #employee #data @JacksonLewisPC
A partnership built on trust. Extended for the long run. We’re proud to extend our partnership with @TeamLiquid for 5 more years, setting a new benchmark for data-driven collaborations in esports. This is what real progress looks like. #Shikenso #Esports #Data #Partnership
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