Statistics Awards

  (Bloomberg ) -- Private-sector companies are beefing up their alternatives to US government statistics, seizing a moment of uncertainty around federal data. One platform is providing its data free to the public, a major break from what’s otherwise largely been a for-profit enterprise. Others are investing in their statistics and publishing them more frequently, responding to client demands for real-time information at a time when government policy, and the economy at large, are rapidly changing. That’s making economists and traders more receptive to private indicators, even though government data remains the gold standard due to its breadth and depth of measuring the world’s largest economy. What’s more, President Donald Trump’s abrupt firing of the head of the Bureau of Labor Statistics — the traditionally apolitical agency responsible for producing key inflation and labor market data — and the perceived partisanship of his pick to replace her has some investors wary of its dat...

  What Are Descriptive Statistics? Descriptive statistics are brief informational coefficients that summarize a given dataset, which can be either a representation of the entire population or a sample of a population. Descriptive statistics are broken down into measures of central tendency and measures of variability (spread). Measures of central tendency include the mean, median, and mode, while measures of variability include standard deviation, variance, minimum and maximum variables, kurtosis, and skewness. Key Takeaways Descriptive statistics summarize or describe the characteristics of a dataset. Descriptive statistics consist of three basic categories of measures: measures of central tendency, measures of variability (or spread), and frequency distribution. Measures of central tendency describe the center of the dataset (mean, median, mode). Measures of variability describe the dispersio...

  In recent weeks, tensions have been escalating between India and the United States over trade issues, particularly with Russia's trade relationship with India. This has come amid threats from President Trump to impose tariffs on Indian goods. In response, India has taken a stand, hitting back at both the EU and the U.S. India doesn't seem to be pleased with US President Donald Trump's 25% tariff on India, threats of further levies, further penalties, and taunts that India is a "dead economy." In addition to claiming that India is a "bright spot" in the global economic landscape, the Indian administration is denouncing the duplicity of Western nations such as the US and the EU about their oil trade with Russia. As far as the bilateral trade between the US and India is concerned, the total trade between the US and India reached $132.98 billion in 2024 and $39.1 billion in the first quarter of 2025, as per the US export data and...

  Understanding differences between BOP and ITGS Due to the different concepts applying to BOP and ITGS, differences in the statistical products are most likely. These differences can arise from transactions in goods that either do not physically cross borders, or that do not involve a change of ownership although being shipped across borders. Additionally, valuation differences can also impact comparability. In order to better understand the conceptual impact, we will discuss selected items of particular relevance . Figure 1: Goods traded under merchanting Source:  Eurostat Manual on goods sent abroad for processing Goods not crossing borders Goods that are not shipped across borders are usually not covered in IMTS. When a change of ownership takes place, however, the BOP compiler has to collect these items separately and add them to BOP transactions in goods. For the following items, separate recording in BOP statistics under the goods account is foreseen by th...

  1. Python’s Built-in Statistics Module: Quick and Easy Stats Python’s built-in statistics module provides simple functions for calculating mean, median, mode, variance, and more. It is perfect for quick statistical analysis without any external dependencies, making it a handy tool for small datasets and basic exploratory work. import statistics as stats   2. NumPy: The Foundation of Numerical Computing NumPy is the backbone of scientific computing in Python. It is the most widely used package, and most machine learning and data analytics Python packages depend on it. NumPy offers powerful array operations, mathematical functions, and random number capabilities, making it essential for statistical analysis and data manipulation.     3. Pandas: Data Analysis and Manipulation Made Simple Pandas is the go-to library for data manipulation and analysis. While working as a data scientist, I use it every day for loading data, processing it, cleaning i...

  G20 merchandise trade, measured in current US dollars, delivered mixed results in Q2 2025, compared with Q1 2025. While exports grew by 2.6%, imports remained broadly unchanged. This was largely due to the sharp contraction in imports into the United States following the earlier surge in imports in Q1 2025. Preliminary estimates indicate sizeable growth in G20 trade in services, 1  with exports and imports rising by 4.7% and 2.9%, respectively, in Q2 2025 (Figure 1 and 2). Trade outcomes in Q2 2025 were influenced by the depreciation of the US dollar against most currencies and rising trade uncertainty, following new tariff announcements. In the United States, merchandise exports increased by 2.7%, supported by higher sales of finished metal shapes and non-monetary gold. However, imports to the US fell sharply, by 18.4%, reflecting a decline in purchases of industrial supplies. This follows the 18.9% increase in imports experienced in Q1 2025. Weaker oil pri...

  The Resolution concerning statistics of work, employment and labour underutilization adopted by the 19th International Conference of Labor Statisticians (ICLS) in 2013 laid the foundation for improved statistical labor standards, by introducing the first international statistical definition of work and a forms-of-work framework distinguishing five forms of work (based on the intended destination of the work and the nature of the transaction): own-use production work, employment, unpaid trainee work, volunteer work, and other work activities. Enabling and promoting the separate measurement of these various forms of work, the 19th ICLS resolution restricts the definition of employment to work done for pay or profit (thus excluding various types of unpaid work that were previously considered employment). The 19th ICLS resolution also refines and expands the measurement of labour underutilization and fosters the analysis of labour market attachment....

  1. Tableau Tableau is a powerful and fast-growing data visualization tool used in the Business Intelligence Industry. It helps simplify raw data into a very easily understandable format. Data analysis is very fast with Tableau; visualizations are like dashboards and worksheets. Features Allows for easy integration with databases, spreadsheets, and big data queries. Offers drag-and-drop functionality for creating interactive and shareable dashboards. Real-world Applications Business intelligence to enhance decision-making. Sales and marketing performance tracking. Supply chain, inventory, and operations management.  2. Apache Spark It is an open-source distributed computing framework that offers a programming interface for managing entire clusters, incorporating automatic data parallelism and fault-tolerance features. Apache Spark is engineered to handle various data processing tasks, including traditional batch processing, as...

  Statistical computing underpins countless scientific advances, yet the field currently lags behind others in harnessing the power of modern high-performance computing infrastructure, despite its potential to accelerate data analysis and modelling. Sameh Abdulah and Ying Sun, both from King Abdullah University of Science and Technology, alongside Mary Lai O. Salvaña of the University of Connecticut, and colleagues, highlight this gap and argue for a stronger connection between the statistical and high-performance computing communities. Their work recognises the growing need for statistical methods to scale with increasingly large and complex datasets, a challenge particularly relevant in fields like artificial intelligence and simulation science. By outlining the historical development of statistical computing, identifying current obstacles, and proposing a roadmap for future collaboration, this research aims to unlock the full potential of high-performance statistical computing a...

  Wages of people in Jersey working in both the public and private sector are higher than in June 2024, a report has found. Statistics Jersey's average earnings report for June 2025 measured the annual change in gross wages and salaries of workers in the island. The report found average earnings had increased by 4.5% in comparison with June last year, but if you take inflation into account, they went up by 1.9%. It said the construction and quarrying industry was the only sector to record a decrease in average earnings, with a decrease of 0.2% on an annual basis. The report found the agriculture and fishing sector had the highest annual increase, up 13.4% on an annual basis, which it said was driven by increased hours and an increase in the minimum wage. Over the last 12 months, the average earnings in the private sector increased by 4.5% in nominal terms but in real terms, after adjusting for inflation, it increased by 1.9%. The average earnings in the public sector, for the same ...

  WhatIs Statistics? Statistics is a way to understand data. By using mathematical analysis and data collection, statistics is used to develop and study various aspects of sets of data. Everything from collecting to interpreting, analyzing, and presenting data is covered in statistics. You don’t have to be a mathematician to use statistics. In fact, this is one field we see in almost every aspect of our lives.  Even something as simple as investing your money or trying to figure out if your favorite sports team has a chance at winning their next game often involves statistics. WhatIs Statistics Used For? Statistics is a field not often thought of as used in the real world, but it is found in a surprising number of industries. From quality testing to predicting disease outbreaks, learning statistics is important. Quality Testing. It is well-known that most companies perform quality tests on their products, but have you ever thought about statistics working ...

  Role Description & Responsibilities Contribute to the Americas Sales Operations team by leading analytics and data science initiatives that transform complex business data into actionable commercial insights. Drive advanced statistical analysis while developing predictive models and machine learning solutions to optimize sales performance and enable data-driven decision making across LATAM markets. Partner with sales leadership to identify analytical opportunities and translate statistical findings into practical business strategies that drive measurable revenue growth. Key responsibilities include: Develop and implement statistical models, machine learning algorithms, and predictive analytics solutions for sales forecasting, pipeline optimization, and customer behavior analysis Build automated data pipelines and reporting systems using Python, R, SQL, and business intelligence platforms (Tableau, PowerBI, Databricks) Lead data science projects including customer seg...

  Part 1: Statistics and Probability   Statistics isn't optional in data science. It's essentially how you separate signal from noise and make claims you can defend. Without statistical thinking, you're just making educated guesses with fancy tools. Why it matters: Every dataset tells a story, but statistics helps you figure out which parts of that story are real. When you understand distributions, you can spot data quality issues instantly. When you know hypothesis testing, you know whether your A/B test results actually mean something. What you'll learn: Start with descriptive statistics. As you might already know, this includes means, medians, standard deviations, and quartiles. These aren't just summary numbers. Learn to visualize distributions and understand what different shapes tell you about your data's behavior. Probability comes next. Learn the basics of probability and conditional probability. Bayes' theorem might look a bit difficult, but it...