Jose Navarro

Taller 1

A brief overview of the title topic, with example plots

Access to safely managed sanitation services is a critical aspect of public health and sustainable development. Understanding the factors influencing sanitation access can provide valuable insights for policymakers and organizations striving to improve sanitation services globally. In this study, I will employ logistic regression analysis to investigate the predictors of safely managed sanitation services. Specifically, Examine the impact of regional, residential, and coverage-related factors on the likelihood of having a safely managed sanitation service. By uncovering these insights, I aim to inform evidence-based policies and interventions to enhance sanitation access and contribute to broader development goals.

Pred vama je analiza ankete istraživanja magazina Kaleidoskop media čiji je cilj bio prikupljanje pouzdanih i relevantnih podataka o izazovima, novinarskim praksama i etičkim dilemama vezanim za upotrebu veštačke inteligencije (VI) u medijima. Anketari u periodu od 21. februara 2024. godine do 20. marta 2024. godine prikupili su odgovore ukupno 109 medijskih radnika.

Welcome to the fascinating realm of consumer analytics, where the heartbeat of retail is interpreted via the prism of data. In this exploratory voyage, I took a deep dive into a large dataset supplied by the UCI Machine Learning Repository. This 'Online Retail II' data set contains all the transactions occurring for UK-based and registered non-store online retail between 01/12/2009 and 09/12/2011.The company mainly sells unique all-occasion gift-ware. Many customers of the company are wholesalers. With almost 525,461 observations spanning eight variables, this dataset holds a wealth of information waiting to be discovered. Each entry in this dataset represents a distinct interaction between the retailer and its broad customer base, collecting a mosaic of transactional information, product features, and consumer demographics. My goal with advanced data analytics and visualization approaches is to extract actionable insights that illuminate strategic paths for retail organizations. My research began with rigorous preprocessing of the dataset, which includes handling missing data, detecting and filtering out cancelled orders, and improving variable forms for consistency and correctness. Moving on, I embarked on an enlightening voyage of exploratory data analysis (EDA), using a variety of visualization tools to uncover the distribution patterns of crucial variables such as quantity, price, and invoice date. I use histograms, time series graphs, and other visual aids to decipher complex purchasing behaviours and identify hidden trends in customer interaction. The next round of my analysis dug further into the essence of customer value by calculating RFM (Recency, Frequency, Monetary) indicators. Using complex K-means clustering algorithms, I divided customers into various cohorts based on their RFM ratings, shedding light on nuanced customer groupings such as high-value customers, regular customers, and inactive customers. Furthermore, I used 'association rule mining' algorithms like Apriori to identify detailed patterns in customer transactions, with an effort to reveal unique insights about product relationships and purchasing habits. Throughout this captivating trip, I provided insightful comments and actionable recommendations at each stage, equipping retail stakeholders with essential insights for refining marketing tactics, improving consumer experiences, and driving long-term business growth. Conclusively, this immersive exploration provides a strong framework for understanding customer behaviour using R in the online retail ecosystem. My analysis acts as a light of information for retail practitioners, providing a road map for navigating the complicated terrain of consumer analytics and realizing the latent potential of online retail.

TidyTuesday 04/02/2024

Access to adequate sanitation is a fundamental human right and a critical determinant of public health and well-being. However, disparities in sanitation access persist globally, with certain regions facing greater challenges than others. Here, I will use statistical methods to analyze regional disparities in access to sanitation services, focusing on two key hypotheses. Firstly, Investigate whether there is a significant difference in the coverage of safely managed sanitation between urban and rural areas. Secondly, Exploring the association between region and the type of sanitation service provided, particularly focusing on whether there are regional disparities in the prevalence of safely managed sanitation services. By examining these hypotheses, to uncover insights that can inform targeted interventions and policy decisions to improve sanitation access and equity worldwide.