The book has gained popularity due to its:
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The book is divided into 19 comprehensive chapters, systematically building knowledge from the ground up. Here is the detailed table of contents for Statistical Methods (Combined Volume) :
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By following these recommendations, readers can develop a deep understanding of statistical methods and their applications, empowering them to make informed decisions and extract insights from data.
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This serves as the starting point for any analysis, focusing on summarizing sample data through measures of central tendency (mean, median, mode) and dispersion (standard deviation, variance). These tools allow researchers to characterize the "shape" of a dataset before deeper investigation. The book has gained popularity due to its:
The second volume shifts focus toward making predictions and drawing conclusions from data:
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N.G. Das’s Statistical Methods is widely used in universities, particularly across South Asia, for undergraduate and postgraduate courses in commerce, economics, management, and social sciences. The book is celebrated for several reasons: Here is the detailed table of contents for
| | Title | Key Topics Covered | | :--- | :--- | :--- | | 1 | Collection of Data: Classification and Tabulation | Data & Statistics, Variables, Distributions, and Numerical Descriptive Statistics | | 2 | Charts and Diagrams | Visual representation of statistical data using graphs, charts, and diagrams | | 3 | Useful Mathematical Devices | Foundational mathematical tools needed for statistical calculation | | 4 | Frequency Distribution | Organizing raw data into frequency tables | | 5 | Measures of Central Tendency | Mean, median, mode, and other averages | | 6 | Measures of Dispersion | Range, variance, standard deviation, and spread of data | | 7 | Moments, Skewness and Kurtosis | Higher-order statistical measures describing the shape of a distribution | | 8 | Curve Fitting and Method of Least Squares | Finding the best-fit line or curve for a given set of data points | | 9 | Correlation and Regression | Analyzing relationships between variables | | 10 | Interpolation | Estimating unknown values that fall between known data points | | 11 | Theory of Probability | Fundamental rules of probability, random variables, and distributions | | 12 | Theoretical Distributions: Binomial, Poisson, Normal | In-depth study of the most important probability distributions | | 13 | Sampling Theory | Concepts of populations, samples, and sampling distributions | | 14 | Estimation and Test of Significance | Hypothesis testing, confidence intervals, and practical significance | | 15 | Analysis of Variance | ANOVA for comparing means of two or more groups | | 16 | Time Series | Analyzing data collected over time to identify trends and patterns | | 17 | Index Numbers | Measuring changes in price, quantity, or value over time | | 18 | Vital Statistics | Statistical methods related to demography and public health data | | 19 | Statistical Quality Control | Using statistical methods to monitor and maintain the quality of processes |
Understanding variability through range, quartile deviation, mean deviation, and standard deviation.