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Statistical Methods by S. P. Gupta is a popular and comprehensive book on statistics that covers various topics such as probability, sampling, correlation, regression, analysis of variance, and testing of hypotheses. The book is suitable for beginners and non-mathematical persons, as it explains the methods like a story[^1^]. The book has four editions and is published by Sultan Chand & Sons[^1^].
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- Chapter 1: Introduction to Statistics: This chapter explains the meaning, scope, and importance of statistics, as well as the basic concepts and terminology used in statistics.
- Chapter 2: Collection of Data: This chapter discusses the methods and sources of collecting primary and secondary data, as well as the types and characteristics of data.
- Chapter 3: Classification and Tabulation of Data: This chapter describes the methods and rules of classifying and tabulating data into frequency distributions and tables.
- Chapter 4: Diagrammatic and Graphic Presentation of Data: This chapter illustrates the various types and methods of presenting data using diagrams and graphs, such as bar charts, pie charts, histograms, frequency polygons, ogives, etc.
- Chapter 5: Measures of Central Tendency: This chapter explains the concept and properties of central tendency, as well as the different measures of central tendency, such as mean, median, mode, geometric mean, harmonic mean, etc.
- Chapter 6: Measures of Dispersion: This chapter explains the concept and properties of dispersion, as well as the different measures of dispersion, such as range, quartile deviation, mean deviation, standard deviation, coefficient of variation, etc.
- Chapter 7: Skewness, Moments and Kurtosis: This chapter explains the concepts and measures of skewness, moments, and kurtosis, which are used to describe the shape and symmetry of a frequency distribution.
- Chapter 8: Correlation Analysis: This chapter explains the concept and types of correlation, as well as the methods and measures of correlation, such as scatter diagram, Karl Pearson's coefficient of correlation, Spearman's rank correlation coefficient, etc.
- Chapter 9: Regression Analysis: This chapter explains the concept and types of regression, as well as the methods and equations of regression for two variables.
- Chapter 10: Probability: This chapter introduces the concept and rules of probability, as well as the different approaches to probability, such as classical, relative frequency, and subjective probability.
- Chapter 11: Theoretical Distributions: This chapter discusses the various theoretical distributions that are used to model different types of data and phenomena, such as binomial distribution, Poisson distribution, normal distribution, etc.
- Chapter 12: Sampling Theory: This chapter explains the concept and types of sampling, as well as the advantages and disadvantages of sampling over census. It also discusses the sampling techniques and errors involved in sampling.
- Chapter 13: Test of Significance: This chapter introduces the concept and steps of hypothesis testing using different tests of significance for one or two samples. It also explains the level of significance, type I and type II errors,
and p-value in hypothesis testing. - Chapter 14: Chi-Square Test: This chapter explains the concept and applications of chi-square test for testing goodness-of-fit,
independence of attributes,
and homogeneity of proportions. - Chapter 15: Analysis of Variance (ANOVA): This chapter explains the concept and applications of analysis of variance for testing equality
of means among more than two populations or treatments. It also discusses
the one-way ANOVA,
two-way ANOVA,
and factorial ANOVA models.
The book also covers other topics such as time series analysis,
index numbers,
vital statistics,
quality control,
decision theory,
non-parametric tests,
etc. The book is a useful resource for students
and practitioners
of statistics
and related fields.