CentralStatz Statistical & Data Sciences LLC’s Post

Here’s a new article providing a simple example why more than statistical significance is needed for actionable inference #statistics

Hypothesis Testing: An Intuitive Guide for Making Data Driven Decisions By Jim Frost (Penn State University) In today's data-driven world, we hear about making decisions based on the data all the time. Hypothesis testing plays a crucial role in that process, whether you're in academia, making business decisions, or in quality improvement. Are you ready? Read this book to build a solid foundation for understanding how hypothesis tests work and become confident that you know when to use each type of test, how to use them properly to obtain reliable results, and interpret the results correctly. I use clear, plain English that helps you grasp key concepts while deemphasizing equations. Painlessly learn how to use these tests! By Jim Frost (Penn State University) https://lnkd.in/eTWvzJCn #statistics #dataanalysis

Hypothesis Testing: An Intuitive Guide for Making Data Driven Decisions By Jim Frost (Penn State University) In today's data-driven world, we hear about making decisions based on the data all the time. Hypothesis testing plays a crucial role in that process, whether you're in academia, making business decisions, or in quality improvement. Are you ready? Read this book to build a solid foundation for understanding how hypothesis tests work and become confident that you know when to use each type of test, how to use them properly to obtain reliable results, and interpret the results correctly. I use clear, plain English that helps you grasp key concepts while deemphasizing equations. Painlessly learn how to use these tests! By Jim Frost (Penn State University) https://lnkd.in/eTWvzJCn #statistics #dataanalysis

In this article Dr Nilimesh Halder shares a comprehensive guide to hypothesis testing, have a read! #analystscorner https://lnkd.in/gYa5n-CD #statistics #datascience #hypothesistesting

🔍 Unlocking Insights with Linear Regression Analysis in R 📈 In the realm of data science, the power of predictive analytics is harnessed through robust statistical models. Here’s a snapshot of a recent linear regression analysis I conducted using R. By examining the relationship between advertising spend 💰 and sales 📊, the model reveals key insights: A significant positive correlation suggests that increased advertising spend contributes to higher sales. 📈 An R-squared value of 0.3802 indicates that approximately 38% of the variance in sales can be predicted from the advertising budget. 🔢 The diagnostic plots further validate the model, showing: Goodness-of-fit with the linearity of residuals. ✔️ Homogeneity of variance is consistent across the range of fitted values. 📏 Residuals approximately follow a normal distribution. 📉 A few influential observations are identified, which will be examined further. 🔎 Such analyses are crucial for making data-driven decisions in marketing strategies. 🎯 #DataScience #LinearRegression #PredictiveAnalytics #RStats #BusinessIntelligence #MarketingAnalytics

Hypothesis Testing for Data-Driven Decisions ✅ The Power of Hypothesis Testing ✅ The Foundation of Statistical Inquiry ☑ Establishing Ground Rules ✅ Data Collection and Analysis ✅ Reaching Evidence-Based Conclusions ✅ Shaping Decisions Across Fields ✅ Ensuring Data Integrity and Significance ✅ Hypothesis Testing as a Beacon of Evidence-Based Research #hypothesistesting #datadriven #research #statistics #evidencebased #decisionmaking #sciencedata #quantitativeanalysis #researchmethods #clinicaltrials #socialresearch

Just Published My First Article on Medium: Navigating Key Statistical Analysis Techniques. Check it out and let me know your thoughts! #DataAnalysis #Statistics

This is a very geeky, though very short post. You might not be an expert on analytics but I think you can understand the basic argument: stop studying ever narrower segments of like-minded people and start focusing your analytical engines on situations. Shout out to Craig Lutz.

So, what’s the problem with adding more data to achieve statistical significance? Well… in doing so you increase the probability of obtaining a significant effect by random chance. In other words, you increase the chance of a type I error (i.e., rejecting the null hypothesis when in fact it is true). 📢 Calling all data enthusiasts and researchers! 📊🔍 Check out this blog by Vanessa Cave. The pitfalls of chasing statistical significance: Don’t add more data to make your results significant! Go ahead and give it a read: https://lnkd.in/eb2dvZCP 📚🔥Don't forget to share it with your network! Let's empower each other to make smarter, data-driven choices! 💪🏼💼 #DataAnalysis #ResearchMethodology #ScientificPublication #Transparency #StatisticalSignificance #DataEnthusiasts

Mastering Regression: How to Make Sense of Complex Relationships 🌟 Exciting News! 🌟 I'm thrilled to announce our latest blog post, "Mastering Regression: How to Make Sense of Complex Relationships". 📊💡 This article is a comprehensive guide to understanding and utilizing regression analysis, a powerful statistical tool in the field of data analysis. We'll explore the different types of regression, including simple linear, multiple linear, polynomial, logistic, ridge, lasso, and time series regression. You'll learn how to choose the right technique for your data and research question, and interpret the results to gain valuable insights into the relationships between variables. 📈🔍 Regression analysis has wide-ranging applications in areas like economics, finance, social sciences, healthcare, and marketing. It can be used for predictive modeling, marketing analysis, healthcare research, and economic forecasting. The potential is limitless! 💼💪 If you want to take your data analysis skills to the next level and unlock hidden patterns within your data, this post is a must-read. Don't miss out! Check it out here: [link](https://ift.tt/H6DJbkj). 📚✨ Remember, knowledge is power, and mastering regression will empower you to make data-driven decisions with confidence. Happy reading! 🎉📖 #DataAnalysis #RegressionAnalysis #DataInsights #Analytics https://ift.tt/H6DJbkj