In SSC CGL TIER II papers are conducted on same day. One Paper is of Quantitative Aptitude & second one is English
Subject
|
Questions
|
Maximum Marks
|
Time Duration
|
Quantitative Aptitude
|
100
|
200
|
2 Hours
|
General English
|
200
|
200
|
2 Hours
|
SSC CGL Exam Syllabus 2017 Tier II
- Paper-I: Quantitative Ability
- Paper-II: English Language & ComprehensionPaper
- Paper-III: For Statistics for Investigator Grade-II Post Only
- Paper IV: General Studies (Finance and Economics) for the post of Assistant Audit Officer in Indian Audit & Accounts Department under CAG.
SSC CGL Tier II of the Combined Graduate Level Examination - 2017 will be of Multiple Choice Questions & will be conducted over a period of two days.
Quantitative Aptitude syllabus of Tier I and Tier II is same.
Apart from Tier-I, English Syllabus, two topics are added Active&Passive and Cloze test.
Collection Classification and Presentation of Statistical Data – Primary and Secondary data, Methods of data collection; Tabulation of data; Graphs and charts; Frequency distributions; Diagrammatic presentation of frequency distributions.
Measures of Central Tendency- Common measures of central tendency – mean median and mode; Partition values- quartiles, deciles, percentiles.
Measures of Dispersion- Common measures dispersion – range, quartile deviations, mean deviation and standard deviation; Measures of relative dispersion.
Moments, Skewness and Kurtosis – Different types of moments and their relationship; the meaning of skewness and kurtosis; different measures of skewness and kurtosis.
Correlation and Regression – Scatter diagram; simple correlation coefficient; simple regression lines; Spearman’s rank correlation; Measures of association of attributes; Multiple regression; Multiple and partial correlations (For three variables only).
Probability Theory – Meaning of probability; Different definitions of probability; Conditional probability; Compound probability; Independent events; Bayes’ theorem
.
Random Variable and Probability Distributions – Random variable; Probability functions; Expectation and Variance of a random variable; Higher moments of a random variable; Binomial, Poisson, Normal and Exponential distributions; Joint distribution of two random variables (discrete).
Sampling Theory – Concept of population and sample; Parameter and statistic, Sampling and non-sampling errors; Probability and non-probability sampling techniques (simple random sampling, stratified sampling, multistage sampling, multiphase sampling, cluster sampling, systematic sampling, purposive sampling, convenience sampling and quota sampling); Sampling distribution(statement only); Sample size decisions.
Statistical Inference - Point estimation and interval estimation, Properties of a good estimator, Methods of estimation (Moments method, Maximum likelihood 21 method, Least squares method), Testing of hypothesis, Basic concept of testing, Small sample and large sample tests, Tests based on Z, t, Chi-square and F statistic, Confidence intervals.
Analysis of Variance - Analysis of one-way classified data and two-way classified data. Time Series Analysis - Components of time series, Determinations of trend component by different methods, Measurement of seasonal variation by different methods.
Index Numbers - Meaning of Index Numbers, Problems in the construction of index numbers, Types of index number, Different formulae, Base shifting and splicing of index numbers, Cost of living Index Numbers, Uses of Index Numbers.
Subject
|
Maximum Marks
|
Finance and Accounts
|
80
|
Economics and Governance
|
120
|
