Sr. No.

Course

Semester

Name of Paper

Course Outcomes

1

B.Sc-I

I

Descriptive Statistics – I

The students will acquire knowledge of      

1. Meaning and scope of Statistics, various statistical organizations. 
2. Population, sample and various methods of sampling. 
3. Various measures of central tendencies and dispersion. 
4. Moments, skewness and kurtosis.

Elementary Probability Theory

Students will be able to, 

1. Distinguish between random and non-random experiments. 
2. Use the basic probability rules, including additive and multiplicative laws. 
3. Understand concept of conditional probability and independence of events. 
4. Understand concept of univariate random variable and its probability distributions

Statistical Practical-I

Students will able to; 

1. Acquire knowledge of computations using MS-Excel. 
2. Represent statistical data diagrammatically and graphically. 
3. Compute various measures of central tendency, dispersion, moments, skewness and kurtosis. 
4. Interpret summary Statistics of computer output. 

II

Statistical Methods

The students will acquire knowledge of      

1. The time series data and its analysis.
2. Rates of vital events, its computation and interpretation. 
3.  How to compute and interpret index numbers.
4.  Cost of living index number and its utility.

Discrete Probability Distributions

The students will acquire knowledge of      

1. One point, Two point and Bernoulli distributions.
2. Discrete uniform, Binomial and Hypergeometric distributions. 
3. Poisson, Geometric and Negative binomial distributions.
4. Applications of these distributions in real-life situations.

Statistical Practical-II

After completion of this course, students will be able to:

1. Analysis and interpret time series data.
2. Compute and interpret population mortality, fertility and growth rates.
3.  Compute and interpret price, quantity and value index numbers. 
4.  Understand the applications of discrete probability distributions.

2

B.Sc-II

III

Probability Distribution-I

The students will acquire knowledge of

1. Bivariate discrete distributions with real life situations.
2. Continuous random variable and find the various measures, probabilities using its probability distribution.
3. Transformation of univariate continuous random variable.
4. Some standard continuous probability distributions with real life situations.
5. The relations among the different distributions.

Statistical Methods-I

The students will acquire knowledge of

1. Obtaining multiple linear regression equations and their applications.
2. The concept of multiple correlations, partial correlation and their computations.
3. Need, construction and utility of various index numbers.
4. The concepts related to national income and different methods of estimation of national income.

IV

Probability Distribution-II

The students will acquire knowledge of 

1. Some standard continuous probability distributions with real life situations.            
2. Finding the various measures of continuous random variable and probabilities by using its probability distributions.            
3. The relationships among different distributions.
4. Continuous bivariate r.v.s. and probability distributions of their transformations.
5. Concept of sampling distribution of a statistic.
6. Some sampling distributions of a statistic: Normal, Chi-Square, t and F distributions with their applications and interrelations.

Statistical Method-II

The students will acquire knowledge of 

1. The concept and use of time series analysis.           
2. The meaning, purpose and use of Statistical Quality Control, construction and working of control charts for variables and attributes.
3. Applying the appropriate small sample tests and large sample tests in various situations.

III & IV

Practical Paper-II

Students will able to;  

i. Fit plane of multiple regression, judge for its goodness of fit by residual plot and compute multiple and partial correlation coefficients.

ii.  Know applications of some standard continuous probability distributions.

iii. Know applications of some standard bivariate discrete probability distributions.  

iv. Understand how to obtain random sample from various probability distributions.

iv. Sketch of the p.m.f./p.d.f. for given parameters.

v. Fit and test the goodness of fit of specified distribution for given data.

vi. Test various hypothesis about parameters of specified distribution for given data.

vii. Construct various control charts.

viii. Apply appropriate statistical methods while doing project on real life problems. 

Practical Paper-III

3

B.Sc-III

V

Probability Distributions

The students will acquire,

a)  Knowledge of important univariate distributions such as Rayleigh, Weibull, Linear failure rate, Cauchy, Lognormal, Logistic, Pareto, Power Series Distribution.

b)  Knowledge of Multinomial and Bivariate Normal Distribution.

c)  Knowledge of Truncated Distributions.

d) Information of various measures of these probability distributions.

e)  Acumen to apply standard continuous probability distributions to different situations.

Statistical Inference - I

The students will acquire

a) Knowledge about important inferential aspect of point estimation.

b) Concept of random sample from a distribution, sampling distribution of a statistic, standard error of important estimates such as mean and proportions.

c) Knowledge of various important properties of estimator.

d) Knowledge about inference of parameters of standard discrete and continuous distributions.

e) Concept of Fisher information and CR inequality.

f) Knowledge of different methods of estimation.

Sampling Theory

The students shall get,

a) Basic knowledge of complete enumeration and sample, sampling frame sampling distribution, sampling and non-sampling errors, principle steps in sample surveys, sample size determination, limitations of sampling etc.

b) Concept of various sampling methods such as simple random sampling, stratified random sampling, systematic sampling and cluster sampling. 

c) An idea of conducting sample surveys and selecting appropriate sampling techniques.

d) Knowledge of comparing various sampling techniques.

e) Knowledge of ratio and regression estimators.

R-Programming and Quality Management

The students will acquire,

a) Importance of R- programming.

b) Knowledge of identifiers and operators used in R.

c) Knowledge of conditional statements and Loops used in R.

d) Knowledge of quality tools used in Quality management.

e) Knowledge of process and product control used in Quality management.

VI

Probability Theory & Applications

The students will acquire

a)  Knowledge about order statistics and associated distributions.

b)  Concept of convergence and Chebychev’s inequality and its uses.

c)  Concept of law large numbers and central limit theorem and its uses.

d)  Knowledge of terms involved in reliability theory as well as concepts and measures.

Statistical Inference - II

The students will acquire

a) Concept of interval estimation.

b) Knowledge of interval estimation of mean, variance and population proportion.

c) Knowledge of important aspect of test of hypothesis and associated concept.

d) Concept about parametric and non-parametric methods.

e) Knowledge of some important parametric as well as non–parametric tests. 

Design of Experiments

The students will acquire

a) Knowledge of basic terms used in design of experiments.

b) Concept of one-way and two-way analysis of variance.

c) Knowledge of various designs of experiments such as CRD, RBD, LSD and factorial experiments.

d) Knowledge of using an appropriate experimental design to analyze the experimental data.

Operation Research & Decision Theory

The students will acquire

a) Concept of Linear programming problem.

b) Knowledge of solving LPP by graphical and simplex method.

c) Knowledge of Transportation, Assignment and Sequencing problems.

d) Concept of queuing and decision theory.

e) Knowledge of simulation technique and Monte Carlo technique of simulation.

4

B.Com-II

III

Business Statistics-I

After completion of this course, the students enable,

i) To explain the scope of statistics in business and apply sampling techniques in real life.

ii) To summarize data by means of measures of central tendency and dispersion.

iii) To explain the merits and demerits of various measures of central tendency and dispersion.

iv) To carryout analysis of bivariate data using simple correlation and simple linear regression.

IV

Business Statistics-II

After completion of this course, the students enable to

i) Understand discrete and continuous random variables, their respective probability distributions.

ii) Identify the applications of Binomial, Poisson and normal distributions.

iii) Measure trend and seasonal variations in time series data.

iv) Compute and interpret simple and weighted index numbers.

v) Construct and apply variable and attribute control charts.

5

OE (other than BSc)

I

Open Elective – I

BASIC STATISTICS PRACTICAL-I

After completion of this practical course, the student will be able to:

1. Apply sampling techniques in real life.
2. Perform classification and tabulation of primary data.
3. Represent the data by means of simple diagrams and graphs.
4. Summarize data by computing measures of central tendency.

II

Open Elective – II

BASIC STATISTICS PRACTICAL-II

After completion of this practical course, the student will be able to:

1. Exhibit variation in data by computing measures of dispersion.
2. Demonstrate and interpret correlation between two variables by using Scatter Plot.
3. Compute correlation coefficient between two variables and interpret the values of correlation coefficient.
4. Obtain linear regression of dependent variable on independent variable and hence estimate value of dependent variable for given value of independent variable.