Course Contents

Meaning and definitions of statistics, Descriptive and inferential statistics, Population parameter and sample statistics, Variable and its types, Use of statistics in modern Sociology, Classification of Data, Levels of Measurement, Types, and Sources of Data, Classification and its Types, Aims of Classification, Frequency Distribution, Class-limits, Class boundaries, Class-marks, Class width, Construction of a Group Frequency Distribution Cumulative Frequency Distribution, Measures of Central Tendency, Average, Introduction and Meaning, Criteria of a Satisfactory Average, Arithmetic Mean, Median, Mode, Quartiles, Deciles and Percentiles, Measures of Dispersion, Introduction and Definitions of Dispersion, Types of Dispersion, Range, Mean Deviation, Variance, Quartile Deviations, Standard Deviation, Coefficient of Variance, Correlation and Regression, Introduction, Meaning and Definition of Correlation, Types of Correlation, Pearson Product Moment or, Coefficient of Correlation, Introduction and Types of Regression, Deterministic and Probabilistic Relation or Model, Least Square Regression Equation Y on X and X on Y, The Logic and Types of Sampling, Population, Target Population, Census Method, Sampling, Sample, Sampling Frame, Sampling Bias, Probability Sampling and Non Probability Sampling, Sampling and Non-Sampling Errors, Principles of Sampling, Hypothesis Testing and Parametric Test, Introduction and Meaning of Hypothesis, Formulation and Types of Hypothesis, Acceptance and Rejection Region, Type-1 and Type -II Error, The Significance Level, One-Tailed and Two Tailed Tests, General Procedure for Testing Hypotheses, Test Based on Normal Distribution, Z- and T- Tests and Their Applications, The Analysis of Variance or F-test, One way Analysis of Variance, Two way Analysis of Variance, Non-Parametric Test, Introduction and Meaning, Merits and Demerits of Non-Parametric Tests, Chi-Square and other Non-Parametric Tests, Statistical Inferences and Computer Applications , SPSS and other Computer based Programs

Course Synopsis

Keeping the importance of statistics, the course has been introduced in sociology with the objectives that the students of sociology shall adopt various techniques of data collection, interpretation, report writing and testing of hypothesis in practical manner to produce quality research. The course has been designed in such a way that the students shall take interest in learning of the statistical tools and further enhances their capacity for implementation with the ethical guidelines of research.

Course Learning Outcomes

After taking this course students will have a mastery over sampling techniques. They will be able to explain the principles of data reduction and can judge the quality of estimators. It will help them to choose appropriate methods of inference to tackle real problems.