# CSS Statistics Syllabus

PAPER: STATISTICS (100 MARKS)

Revised Scheme and Syllabus for CSS Competitive Examination-2016

Part – I (50 marks)

I. 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.

II. 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 variables.

III. 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 and Poisson distribution.

IV. 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 and Multiple Correlation (upto

three variables).

V. 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.

Part – II (50 marks)

I. Sampling & Sampling Distributions

Population and Sample, Advantages of Sampling, Sampling Design, Probability

&Non-Probability Sampling techniques.Brief Concepts of Simple Random, Stratified,

Systematic, Cluster, Multiple and Multistage 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.

II. Statistical Inferences

Estimation: Point Estimation, Properties of a good Estimator.Interval Estimation.

Interval Estimation of Population mean. Large and small sample confidence intervals

for Population Mean.

Hypothesis Testing: Types of errors. Hypothesis Testing for Population Mean.

Inferences for Two Population Means. Inferences for the Mean of Two Normal

Populations using Independent Samples (variances are assumed Equal). Inference

for Two Populations Mean using Paired Samples.Inferences for Population

Proportions. Confidence Intervals and hypothesis testing for Population Proportion.

Inferences for Two Populations Proportions using Independent Samples, Estimation

of sample size

Analysis of categorized data.Goodness of fit tests.Contingency tables. Test of

independence in contingency tables.

III. 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).

IV. 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 and

Bureaus of Statistics: The National Income, Gross Domestic Product, Saving and

Wealth, Index Numbers.

Revised Scheme and Syllabus for CSS Competitive Examination-2016

Part – I (50 marks)

I. 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.

II. 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 variables.

III. 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 and Poisson distribution.

IV. 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 and Multiple Correlation (upto

three variables).

V. 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.

Part – II (50 marks)

I. Sampling & Sampling Distributions

Population and Sample, Advantages of Sampling, Sampling Design, Probability

&Non-Probability Sampling techniques.Brief Concepts of Simple Random, Stratified,

Systematic, Cluster, Multiple and Multistage 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.

II. Statistical Inferences

Estimation: Point Estimation, Properties of a good Estimator.Interval Estimation.

Interval Estimation of Population mean. Large and small sample confidence intervals

for Population Mean.

Hypothesis Testing: Types of errors. Hypothesis Testing for Population Mean.

Inferences for Two Population Means. Inferences for the Mean of Two Normal

Populations using Independent Samples (variances are assumed Equal). Inference

for Two Populations Mean using Paired Samples.Inferences for Population

Proportions. Confidence Intervals and hypothesis testing for Population Proportion.

Inferences for Two Populations Proportions using Independent Samples, Estimation

of sample size

Analysis of categorized data.Goodness of fit tests.Contingency tables. Test of

independence in contingency tables.

III. 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).

IV. 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 and

Bureaus of Statistics: The National Income, Gross Domestic Product, Saving and

Wealth, Index Numbers.