PC 2 :Logical, Analytical and Quantitative Abilities (All branches) Duration 2 hours, Maximum Marks: 100
(A) DATA INTERPRETATION—————————————————————————————(70 Marks)
i. Data Tables
ii. Pie Charts
iii. 2 Dimensional Graphs
iv. Bar Charts
v. Venn Diagram
vi. Geometrical Diagram
vii. Pert Charts
(B) DATA SUFFICIENCY
(C) REASONING
i. Deduction
ii. Logical connectives.
iii. Selections
iv. Distribution
v. Circular arrangement
(D) QUANTITATIVE ABILITY
i. Probability and chance
ii. Simple Equation
iii. Ratio-Proportion-Variation
iv. Percentages
v. Profit & Loss
vi. Simple Interest and Compound Interest
vii. Weighted Averages
(E) Statistics & Statistical Sampling ————————————————————————————————————————————————————————–Section II 30 marks
i. Introduction to statistics.:Variable as attribute of an entity, Primary Data and Secondary Data, Descriptive and Numerical Data, Concept of Discrete and continuous data, Basic concepts of Data Analysis,Box plotting of Data
ii. Statistical concepts of classification of Data, Geographical Classification, Chronological classification, conditional classification, qualitative classification, quantitative classification.
iii. Class interval, Frequency Distribution and Histograms
iv. Arithmetic Mean and Geometric Mean, Median, Mode-Concepts and inter se comparison and their interpretation
v. Range, Variance, Standard Deviation, Quartile Deviation and Coefficient on Variance – Concepts & inter se comparison and their interpretation
vi. Concepts of Skewness& Kurtosis and their interpretation
vii. Sampling:
What is Statistical Sampling?
Statistical Sampling vs. Non- Statistical Sampling Advantage of Statistical Sampling
Random Number Table & Sampling
Sampling Error vs. Non-Sampling Error
Simple Random Sampling (with and without replacement)Systematic Random Sampling
Systematic Random Sampling Stratified Random Sampling Cluster Sampling
Probability Proportional to Size Sampling Multi-Stage Sampling
Attribute & Variable Sampling Step-by-step Sampling
Discovery Sampling
Monetary Unit Sampling Audit Hypothesis Testing
Normalisation – meaning and objective Estimation:
(i) Sample size and estimation of Single Mean for un-stratified (Simple Random) Sampling
(ii) Sample size and estimation of Single Proportion for un-stratified (Simple Random) Sampling
Scatter Diagram in Statistics and interpreting, Scatter Diagrams, correlation and regression.