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Wheelan uses real-life examples, humor and relatable explanations to demystify complex statistical concepts, making them accessible for all. By reading this books, you should be able to cover topics such as probability, regression, analysis, sampling and the pitfalls of interpreting data in a manner that would be relatable.
–How to draw valid and useful conclusions from your data. –How to create publication-quality graphics of your results. Combining detailed explanations with real-world examples and exercises, this book will provide you with a solid understanding of both statistics and the depth of R’s functionality.
Statistical inference is the process of using a sample to infer the properties of a population. Statistical procedures use sample data to estimate the characteristics of the whole population from which the sample was drawn.
The basic concepts of statistical inference are introduced and three main problems are stated, namely, Point Estimation, Hypothesis Testing, and Construction of Confidence Sets. This is followed by a unified approach of Statistical Decision Theory. We then discuss Sufficient Statistics and the Factorization Theorem.
18 wrz 2020 · In a stratified sample, researchers divide a population into homogeneous subpopulations called strata (the plural of stratum) based on specific characteristics (e.g., race, gender identity, location, etc.). Every member of the population studied should be in exactly one stratum.
18 sie 2009 · 1 - Sampling methods. Published online by Cambridge University Press: 18 August 2009. Sergey Dorofeevand. Peter Grant. Show author details. Chapter. Book contents. Get access. Share. Cite. Summary. This book is about the statistical aspects of sample surveys.
3 sty 2022 · In this article we share 8 examples of how statistics is used in real life. Related: Why is Statistics Important? (10 Reasons Statistics Matters!) Example 1: Weather Forecasting. Statistics is used heavily in the field of weather forecasting.
