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Indradhanu (Jibanara SaptaRanga)

185.00
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INDUSTRAL PHARMACY-II

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INDUSTRIAL PHARMACY

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INDUSTRIAL PHARMACY – I

499.00
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Ink Of Unity Republic Rhapsodies

349.00
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INSPIRED RESOLUTION

349.00
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INSTRUMENTAL METHODS OF ANALYSIS

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INTERNET AND WEB DESIGNING

499.00
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Introduction to General Pharmacy

499.00
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INTRODUCTION TO THEORY OF STATISTICS

499.00
This book, Introduction to Theory of Statistics, provides a foundational and advanced exploration of the core principles that govern statistical analysis. Beginning with Chapter 1: Theory of Probability, the text introduces the fundamental concepts of chance, randomness, and the axiomatic foundations of probability that serve as the bedrock of statistical reasoning. Chapter 2 delves into Random Variables and Distribution Functions, emphasizing both discrete and continuous variables and the rules governing their distributions. Chapter 3 builds on this by exploring Expectations and Moments, offering insight into key statistical measures such as the mean, variance, skewness, and kurtosis, which describe the central tendency and shape of data distributions. Moving forward, Chapter 4 focuses on Distribution Functions, presenting detailed studies of probability distributions and their real-world applications. Chapter 5 addresses Continuous Distributions, introducing vital continuous probability models such as the normal, exponential, and gamma distributions, which are instrumental in various fields of research and industry. The comprehensive nature of the text is further exemplified in Chapter 6, which covers Joint and Conditional Distributions, Stochastic Independence, and Advanced Expectations, facilitating a deeper understanding of how random variables interact and influence one another. Finally, Chapter 7 discusses Sampling Methods, Sample Mean, and Population Estimation, where the theory meets practical application. It examines different sampling techniques, the importance of sample statistics, and how these are used to estimate and infer characteristics of larger populations. This chapter bridges theoretical statistics and empirical analysis, highlighting estimation procedures and the significance of inferential statistics in research and decision-making. Overall, the book is structured to build statistical literacy progressively, supporting learners in developing both conceptual clarity and applied skills necessary for advanced study and real-world data analysis.
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INTRODUCTION TO THEORY OF STATISTICS

499.00
This book, Introduction to Theory of Statistics, provides a foundational and advanced exploration of the core principles that govern statistical analysis. Beginning with Chapter 1: Theory of Probability, the text introduces the fundamental concepts of chance, randomness, and the axiomatic foundations of probability that serve as the bedrock of statistical reasoning. Chapter 2 delves into Random Variables and Distribution Functions, emphasizing both discrete and continuous variables and the rules governing their distributions. Chapter 3 builds on this by exploring Expectations and Moments, offering insight into key statistical measures such as the mean, variance, skewness, and kurtosis, which describe the central tendency and shape of data distributions. Moving forward, Chapter 4 focuses on Distribution Functions, presenting detailed studies of probability distributions and their real-world applications. Chapter 5 addresses Continuous Distributions, introducing vital continuous probability models such as the normal, exponential, and gamma distributions, which are instrumental in various fields of research and industry. The comprehensive nature of the text is further exemplified in Chapter 6, which covers Joint and Conditional Distributions, Stochastic Independence, and Advanced Expectations, facilitating a deeper understanding of how random variables interact and influence one another. Finally, Chapter 7 discusses Sampling Methods, Sample Mean, and Population Estimation, where the theory meets practical application. It examines different sampling techniques, the importance of sample statistics, and how these are used to estimate and infer characteristics of larger populations. This chapter bridges theoretical statistics and empirical analysis, highlighting estimation procedures and the significance of inferential statistics in research and decision-making. Overall, the book is structured to build statistical literacy progressively, supporting learners in developing both conceptual clarity and applied skills necessary for advanced study and real-world data analysis.
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Ipsita Swarga

189.00
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Ipsita Swarga

189.00
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Iyaṟkaiyiṉ ōviyam

349.00
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