CSS Statistics Syllabus

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.


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