SKU/Artículo: AMZ-B0FK4F57H6

Foundations of Data Science and Statistics: Analytics Made Simple (Science, Math, Engineering, and Technology (STEM))

Format:

Paperback

Kindle

Paperback

Detalles del producto
Disponibilidad:
En stock
Peso con empaque:
0.85 kg
Devolución:
Condición
Nuevo
Producto de:
Amazon
Viaja desde
USA

Sobre este producto
  • Learn statistics for beginners, business, and data science — without the confusion. Whether you’re a student, professional, or entrepreneur, Foundations of Data Science and Statistics: Analytics Made Simple gives you a clear, practical path to mastering the most important statistical concepts. This guide blends theory and application so you can use statistics to solve real-world problems, make data-driven decisions, and improve your analytical skills. Includes sections about econometrics, ARIMA, ANOVA, clustering, machine learning, neural networks, and so much more.Inside, you’ll find:Beginner-friendly explanations of descriptive statistics, probability basics, and inferential methods.Practical statistics techniques you can apply in business, economics, and everyday decision-making.Step-by-step guidance on statistical analysis for data science projects.Examples and exercises designed for self-study, classroom learning, or workplace application.Applied statistics tools for business analytics, economics research, and performance improvement.No complicated jargon. No overwhelming formulas. Just clear, easy-to-follow lessons that help you build confidence in statistics and analytics — even if you’ve never enjoyed math before.If you need a statistics workbook, a statistics crash course, or a practical statistics guide you can use right away, this book delivers. Whether your goal is to pass a statistics course, analyze business data, or explore data science, you’ll learn skills you can apply immediately.Perfect for:Beginners who want a quick yet thorough introduction to statistics.Business professionals who need to understand data.Students in economics, data science, or related fields.Self-learners seeking a step-by-step guide to statistics and analytics.Master statistics for data science, business, and economics — and turn numbers into knowledge.
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