magic numbers’ Post

Don’t be misled by a colourful map… it’s very easily done. A few weeks back, Labour recorded a landslide victory in the general election, but that doesn’t look to be the case according to the chart on the left. You could easily conclude, looking at it, the Tories actually won! But why is this the case? Constituencies are far from evenly distributed around the UK and there tend to be more in areas with greater population. Cities, therefore, are packed with lots of smaller constituencies which you can’t see on geographically correct maps, because they’re all on top of each other.🏙️ Cartograms, like the map on the right, fix it because they standardise constituency area. All constituencies are worth one seat no matter how big they are, so making their size in the picture equal just makes more sense! The right-hand side in our diagram shows a better visualisation of the election results data. Where the vast majority of inner-city seats were won by Labour, there is now much more red. Have you been misled by any other coloured maps like this? Are you sure? 🚩Interpreting, visualising and communicating data is just as important in marketing as it is in politics. If you want to get better at it, you should check out our course Data Works starting 8th October. Link in comments or for groups or questions talk to Imogen Howard via [email protected] For analytics consultancy email [email protected] #marketing #training #data

Don’t be misled by a colourful map… it’s very easily done. A few weeks back, Labour recorded a landslide victory in the general election, but that doesn’t look to be the case according to the chart on the left. You could easily conclude, looking at it, the Tories actually won! But why is this the case? Constituencies are far from evenly distributed around the UK and there tend to be more in areas with greater population. Cities, therefore, are packed with lots of smaller constituencies which you can’t see on geographically correct maps, because they’re all on top of each other.🏙️ Cartograms, like the map on the right, fix it because they standardise constituency area. All constituencies are worth one seat no matter how big they are, so making their size in the picture equal just makes more sense! The right-hand side in our diagram shows a better visualisation of the election results data. Where the vast majority of inner-city seats were won by Labour, there is now much more red. Have you been misled by any other coloured maps like this? Are you sure? 🚩Interpreting, visualising and communicating data is just as important in marketing as it is in politics. If you want to get better at it, you should check out our course Data Works starting 8th October. Book now and ready more here: https://lnkd.in/eiTk5Qq5 or for groups or questions talk to Imogen Howard via [email protected] For analytics consultancy email [email protected] #marketing #training #data

Unpicking some of the election data is a great example of how using different tests can show vastly different results. In my latest article for Elite Franchise I've shared 6 practical tips for avoiding these pitfalls in any data project 👇

I'm once again honored to be a contributor to the President's Budget and the associated analytical perspectives chapters. Highlights include support for public access and secure access to data! "The Budget includes funding at multiple agencies for the infrastructure and capacity to provide free, immediate, and equitable public access to federally-funded research results, while developing mechanisms to incentivize and reward open, reproducible, and secure research practices, in ways that benefit individuals, industry, and innovators everywhere." https://lnkd.in/eqzcgkty "Today, the Federal statistical system collects and transforms data into useful, objective information and makes it readily and equitably available to stakeholders, while protecting the responses of individual data providers." https://lnkd.in/eTsMMt8r

From the Government Documents Roundtable of ALA [GODORT of American Library Association]: Not only does data.gov have government data sets, but you can also find sets on Open ICPSR. Some particularly cool information about "Sprouting Cities: How Rural America Industrialized" that used US census data from 1880-1940 to study urbanization. See the data here: https://lnkd.in/gwkprGNB Citation: Eckert, Fabian, Juneau, John, and Peters, Michael. Data and Code for “Sprouting Cities: How Rural America Industrialized.” Nashville, TN: American Economic Association [publisher], 2023. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2023-05-01. https://lnkd.in/g2YvEQtD

In today's instalment of interpreting data we ask ourselves 'What is the data not telling me?' I am sure that much of the time when people are puzzled by data visualisations, they're looking for things that aren't there. The data cannot tell us everything, and a single visualisation definitely can't; being aware of what the data doesn't tell you will help you use what it does. For example, if you're looking at survey data it might tell you how many people gave an answer but does it tell you what kind of people answered the survey? A service level agreement might tell you the number of contacts answered on time, but does it include the number never answered at all? At last year's elections in the UK we were told the number of people turned away from poll stations due to not having identity documents, but there's no way of counting the people who would have voted but didn't go because they didn't have the right documents - you can't count what's not there. (See how I sneaked in a reminder to get your voter ID/postal vote sorted out if you need it?) Take a moment to think about what the data doesn't tell you and decide what, if anything you want to do about it. Maybe just knowing what isn't there is enough to help you use what is there. On the other hand, if you need to know more then go and ask your data analyst for more information. Come back for more tomorrow but if you can't wait until then, download my free ebook and see how you can 'feel greater about data'. https://lnkd.in/eCRhvMiB

How have the election results and Labour Party (UK) Keir Starmer 's win last week influenced the public view on the UK Government? Let's find out... How we collected the data 👇 To provide a fair and unbiased study, we avoided looking at keywords associated with specific parties, and instead used broad keywords to examine general public feelings on UK politics over the election period. For example: "Prime Minister" "UK Government" "British Politics" Were some of the keywords used in the study. Where does Exorde's data come from? 👇 We examine data over 5000+ sources every day, analysing roughly 5 million posts from news and social media sources daily. For this analysis, we restricted our data to social media sources only. This was to avoid the analysis being influenced paid or influenced PR activity from news channels, and more accurately capture public sentiment on the topic. What we found 👇 Public sentiment analysis showed huge rises of positivity as the Labour lead became increasingly apparent. During and after the election day, this positivity and optimism remained high, suggesting an excitement and optimism for the new UK leadership. For more information, leave a comment on this post or contact us direct: https://lnkd.in/e2YAnUDE #UKpolitics #politics #labour #labourparty #keirstarmer #politicaldata #pollingdata #datascience #data #dataanalytics #sentimentdata The Labour Party UK government

🚀 Excited to share my latest project: an Election Analysis Dashboard created using Power BI! 🎉 This dashboard provides a detailed and visually engaging overview of the Indian general elections of 2014 and 2019, highlighting the performance of the major political parties: BJP (Bhartiya Janata Party) and INC (Indian National Congress). Key Features: 🔹 Seat Distribution & Vote Shares: Clear visualization of the number of seats won and vote shares across both elections. 🔹 Comparative Margins: Detailed comparison of vote margins between BJP, INC, and other parties, providing insights into shifting political landscapes. 🔹 Constituency Performance: Comprehensive data on party performance across various constituencies, enabling in-depth analysis of regional trends. Dashboard Highlights: 📊 Seats Analysis: Comparison of seats won by major parties in 2014 vs. 2019. 📊 Vote Share Analysis: Visualization of the total votes received by each party. 📊 Margin Analysis: Detailed look at the margins of victory for BJP and INC. 📊 Constituency Breakdown: Performance of parties in individual constituencies. This project underscores the power of data visualization in transforming complex electoral data into actionable insights, enabling better understanding and storytelling of election dynamics. Check out the dashboard below! 👇 #PowerBI #DataVisualization #BigData #Analytics #DataScience #Election2024 #ElectionResults #IndianElections #PoliticalAnalysis #DataStorytelling #India #Politics #BJP #INC #ElectionAnalysis #DataInsights #Technology #Innovation

How you use and talk about data is just as important the research itself. An interesting piece by Royal Statistical Society chief executive Sarah Cumbers MSc PhD about enhancing how governments use statistics. Robert Chote, the chair of the UK Statistics Authority says that statistical claims should enhance understanding, rather than being used in a way that could be misleading. We couldn't agree more. It's good to see that transparency, accuracy, and better communication of stats is making headlines. Read more 🔗👇 #DataDriven #MarketResearch #PublicPolicy #DataTransparency

We couldn't agree more with this comment piece from UK Statistics Authority chair, Robert Chote 👏 👏 👏 📖 Read our briefing to learn how more data sharing across government can improve public services and decision-making & drive efficiency savings: https://lnkd.in/ejYwPTAr