# STATISTICS BCS SYLLABUS FOR WRITTEN EXAMINATION

STATISTICS BCS SYLLABUS FOR WRITTEN EXAMINATION

Part-I, Marks – 100

1. Introduction to Statistics:

Definition and scope, Scope of Statistics, Classification, Variables.

2. Presentation of Data:

Charts or Diagrams, Types of diagrams.

3. Grouping Data:

Frequency Distribution, General rules for forming frequency, Graphical presentation of frequency distribution, Relative frequency distribution.

4. Measures of Central Tendency:

The Arithmetic mean, the Median, The Mode, The Geometric Mean. The Harmonic Mean, Finding Measures of Central tendency from Grouped data, Graphical determination of Measures of Central tendency, Comparative discussion on measures of central tendency.

5. Measures of Dispersion:

Dispersion or variation, Measures of dispersion from grouped data, Interpretation of Standard deviation, Chebyshev rule, Normal rule, Relative dispersion: Co-efficient of Variation.

6. Skewness and Kurtosis:

Skewness, Kurtosis, Skewness and kurtosis from graphical displays, Descriptive measures of skewness and kurtosis.

7. Regression and correlation:

Simple regression and correlation. Least squares estimates of simple linear regression, regression coefficient and correlation coefficient. Rank correlation, correlation ratio and partial correlation. Multiple regression and multiple correlation coefficient. Coefficient of determination.

8. Demography:

Crude birth and death rates, Fertility rate, Age specific and total fertility rates, Population growth in Bangladesh, Migration, Nuptiality.

9. Index Number:

Definition, Properties of index numbers, Significance of index numbers, Classification of index numbers, Simple Index Number, Un weighted indices, Simple average of price index, Simple Aggregate Index, Weighted Indices, Laspeyres index, Paasche method, Fisher’s Ideal Index, Weighted average of relatives.

10. Time Series Analysis:

Components of a time series. Measurement of secular trend, seasonal variations, cyclical variations and measurement of irregular variations.

11. Sampling:

Statistical population and sample. Advantages and disadvantages of sampling over census. Sample design. Probability and non-probability sampling. Simple random sampling, stratified random sampling and systematic sampling. Cluster sampling, sampling error and non-sampling error. Determination of sample size.

STATISTICS BCS SYLLABUS

Part-II, Marks – 100

1. Concept of probability:

Basic Definitions, Approaches of Defining probability, Basic properties of probabilities, Notation and Graphical displays for events.

2. Rules of Probability:

Special Addition rule, The complementary Rule, General Addition rule, Bi variate data and Contingency table. Joint and marginal probabilities, Multiplication rules, Conditional probabilities, Concept of Bayes’ Theorem.

3. Random Variables and probability Distributions:

Random variable, Discrete Probability Distribution, Binomial Probability, Hyper geometric distribution, Poisson distribution, Normal distribution.

4. Sampling Distribution:

Sampling distribution of the sample mean for a normally distributed variable, The Central Limit Theorem (CLT), Sampling Distribution of the Sample Mean, Sampling distribution of the sample proportion, Sampling distribution of function of mean and proportion. Confidence interval, Confidence interval of Population mean. Determination of Sample size, Sampling for estimating mean, Sampling for estimating proportion.

5. Basic Concepts of Hypothesis Testing :

Null and Alternative hypothesis, simple and composite hypotheses, Test statistic, acceptance and rejection regions, type I and type II errors, the significance level, one tailed and two tailed tests, general procedure for test of hypothesis. Tests based on normal, student’s t, F, and X2 distribution. The Z- test for two population means. The pooled t-test for two population means. The paired t-test for two population means.

6. Analysis of Variance:

Concept of analysis of variance, treatment, response, extraneous variables, One-Way Anova Model, Estimate of The Model Parameters, Hypothesis Testing In Anova. Two-Way Anova, significance of Correlation and rank correlation coefficients. Multiple comparison test. Two-way analysis of variance with and without interaction.

7. Experimental Designs:

Basic principles of Experimental Design. Randomization, Replication and Local control. The completely Randomized Design (CRD), Randomized Complete Block Design (RCBD) and Latin square Design.