CSS Statistics 2025 Group 2

CSS Statistics Syllabus 2025

This article covers the CSS Statistics complete Syllabus 2025.

The syllabus of CSS Statistics consists of 2 parts of a collective 100 marks i.e.50 marks each.

The examination for CSS Statistics is the Group 2 exam for CSS candidates.

CSS Statistics Syllabus 2025

Paper-I (50 Marks)

Descriptive Statistics: 

• • Definition, 
  • Importance and scope of Statistics, 
  • Descriptive and Inferential Statistics, 
  • Presentation of the Data, Tables, Graphs and Charts: Stem-and leaf diagram, Box and Whisker Plots. 
  • Measures of Central Tendency/location, 
  • Measures of Dispersion/Variability: Measures of Skewness and Kurtosis.

Basic Probability:

• • Basic Probability Concepts, 
  • Additive and Multiplicative laws of Probability, 
  • Joint and Marginal Probabilities, 
  • Conditional Probability and Statistical Independence, 
  • Bayes’ rule. 
  • Concept of a Random Variable, 
  • Mathematical Expectations, 
  • Discrete and Continuous Random Variables, 
  • Probability Distribution, 
  • Mean and Variance of a discrete random variable.

Probability Distributions: 

• • Discrete and continuous Probability Distributions.
  • Properties, applications of Binomial, 
  • Poisson, 
  • Hyper-geometric, 
  • Normal Distribution and its properties, 
  • Standard Normal Curve, 
  • Normal approximation to Binomial 
  • Poisson distribution.

Regression Analysis & Correlation Analysis:-

• • Concepts of Regression and Correlation and their application, 
  • Simple and Multiple Linear Regression (upto three variables), 
  • Estimation of the Parameters, 
  • Method of least square, 
  • Inference regarding regression parameters
  • Correlation, 
  • Correlation Coefficient, 
  • Properties of Correlation Coefficient, 
  • Inference regarding correlation coefficient, 
  • Partial Correlation 
  • Multiple Correlation (upto three variables).

Non-Parametric Methods:-

• • Parametric versus nonparametric tests, when to use non-parametric procedures,
  • One-sample tests: Sign test, 
  • Wilcoxan signed ranks tests, 
  • Kolmogrov-Smirnov test, run test.
  • Tests for two related samples: sign test, run tests, chi-square test, 
  • Test for two independent samples: Mann-Whitney test, 
  • Kolmogrov-Smirnov test.

Paper-II(50 Marks)

Sampling & Sampling Distributions: 

• • Population and Sample, 
  • Advantages of Sampling, 
  • Sampling Design, 
  • Probability & Non-Probability Sampling techniques. 
  • Brief Concepts of Simple Random, Stratified, 
  • Systematic, 
  • Cluster, 
  • Multiphase and Multistage Sampling. 
  • Nonprobability sampling: Purposive, 
  • Quota Sampling, 
  • Convenience & Accidental Sampling. 
  • Sampling with and without replacement, 
  • Application of Central Limit Theorem in Sampling, 
  • Sampling Distribution of Mean, 
  • Difference between two Means, 
  • Proportion, 
  • Difference between two Proportion and Variance.

Statistical Inferences: 

• • Estimation: Point Estimation, 
  • Properties of a good Estimator. 
  • Interval Estimation. 
  • Interval Estimation of Single Population means and Single proportion. 
  • Difference between two means and Difference between two proportions. 
  • Hypothesis Testing: Types of errors. 
  • Hypothesis Testing for Population Mean. 
  • Inferences for difference between Two Population Means. 
  • Inferences for the difference between Means of Two Normal Populations using Independent Samples (Variances are assumed Equal) for sample size. 
  • Inference for Two Populations Mean using Paired Samples. 
  • Hypothesis testing for Single Population Proportion and difference between two population proportions. 
  • Estimation of sample size. 
  • Analysis of categorized data. 
  • Goodness of fit tests. 
  • Contingency tables. 
  • Test of independence in contingency tables.

Design of Experiments:

• • One-way and Two-way Analysis of Variance, 
  • Design of Experiments, 
  • Concepts of Treatment, 
  • Replication, 
  • Blocking, 
  • Experimental Units and Experimental Error, 
  • Basic Principles of Design of Experiments, 
  • Description, 
  • Layout and Statistical Analysis of Completely Randomized Design (CRD),
  • Randomized Complete Block Design (RCBD), 
  • Multiple Comparison tests (LSD test). 

Population Analysis & Vital Statistics

• • Population and Demographic Methods, 
  • Sources of Demographic data, Basic Demographic Measures, 
  • Sex Ratio, 
  • Child Women Ratio, 
  • Vital Index, 
  • Crude and Specific Birth and Death Rates, 
  • Total Fertility and Net Reproduction Rates. 
  • Official Statistics: Statistical Systems in Pakistan, 
  • Functions of Statistics Division, 
  • Bureaus of Statistics and NADRA. 
  • The National Income, 
  • Gross Domestic Product, 
  • Saving and Wealth, 
  • Index Numbers

This is the complete syllabus for preparation of CSS Statistics.

The Candidates should prepare thoroughly to succeed in the examination.

Therefore, here are a few suggested books you can buy for better learning about CSS Statistics from your favorite Multan Kitab Ghar online bookstore.

Suggested Reading Books for CSS Statistics 2025

• Principles and Procedures of Statistics by Steel, R and Torrie, J.H.
• Biostatistical Analysis by Zar, J.H.
• Probability and Statistics for Engineers and Scientists by  Walpole, R.E., Myers, R.H. and Myers, S.L.
• Introduction to Statistical Theory, Part-I & II by Chaudhry, S.M. and Kamal, S.
• Introduction to Probability Theory and Statistical Inference, 3rd Edition by Larson, H.J.
• Design and Analysis of Experiments by Montgomery, D.C.
• Fundamentals of Modern Statistical Methods by Wilcox, R.
• Latest Statistical Methods by Vaidyanathan, M.
• Statistical Methods by Aggarwal, Y.P.
• Mathematical Statistics by Freund, John E.
• Demographic Methods by Andrew Hinde
• Publications of Federal Board of Statistics and Provincial Board of Statistics, Pakistan by Govt. of Pakistan