statsdept

B.A/B.Sc. III Year V Semester (CBCS): Statistics Syllabus Practical – 5(A) : Applied Statistics - I [Credits 1 and 50 Marks] Practical using R – Software and MS – Excel R – Software : Overview of R, R data types and objects, reading and writing data, sub setting R Objects, Essentials of the R Language, Running R, Packages in R, Variable names and assignment, Operators, Integers, Factors, Logical operations. Operations of Scalars, Vectors, Lists, Arrays, Matrices, Data Frames. Control structures, Functions. 1. Data Visualization using R - Frequency polygons and curves, Ogives, Histogram using R. 2. Data Visualization using R - Bar diagrams (simple, compound, percentage and multiple) and Pie diagram (single and multiple) using R. 3. Computation of Descriptive Statistics using R (Measures of Central tendencies and Dispersion, Moments, Skewness and Kurtosis) using R. 4. Computation of expected frequencies for Binomial, Poisson, Normal and Exponential distributions using R. 5. Computation o

  B.A/B.Sc. III Year V Semester (CBCS) : Statistics Syllabus Paper – V(A) : Applied Statistics - I [4 Credits :: 100 Marks (External : 80, Internal : 20)] UNIT-I Sample Surveys: Concepts of population, sample, sampling unit, parameter, statistic, sample frame and standard error. Principal steps in sample surveys - need for sampling, census versus sample surveys, sampling and non- sampling errors, sources and treatment of non-sampling errors, advantages and limitations of sampling. Sampling Methods: Types of sampling: Subjective, probability and mixed sampling methods. Methods of drawing random samples with and without replacement. Estimates of population mean, total, and proportion, their variances and the estimates of variances in Simple Random Sampling With and Without Replacement UNIT-II Estimates of population mean, total, and proportion, their variances and the estimates of variances in the following methods. (i) Stratified Random Sampling with Proportional and Neyman allocation,

B.A/B.Sc - II Year,  III Semester (CBCS): Statistics Syllabus Paper – III: Statistical Methods and Theory of Estimation [4 Credits :: 100 Marks (External:80, Internal:20)] Unit –I Bivariate data, Scattered diagram, Principle of least squares, fitting of straight line, quadratic and power curves. Concept of correlation, computation of Karl-Pearson correlation coefficient for grouped and ungrouped data and its properties. Correlation ratio, Spearman’s rank correlation coefficient and its properties. Simple linear regression, correlation verses regression, properties of regression coefficients. Unit –II Concepts of partial and multiple correlation coefficients (only for three variables). Analysis of categorical data, their independence, Association and partial association of attributes. Various measures of association: Yule’s coefficient of colligation and  Pearson and Tcherprow coefficient of contingency for two way data. Unit – III Concepts of Population, Parameter, Random sample, Stati

B.A/B.Sc - I Year, I Semester (CBCS) : Statistics Syllabus Paper – I: Descriptive Statistics and Probability [4 Credits :: 100 Marks (External:80, Internal:20)] Unit-I Descriptive Statistics: Concept of primary and secondary data, Classification of data, Measures of central tendency (Arithmetic mean, median, mode, geometric mean and harmonic mean) with simple applications, Absolute and relative measures of dispersion (range, quartile deviation, mean deviation, standard deviation and variance) with simple applications. Importance of moments, central and non-central moments, their inter-relationships, Sheppard’s correction for moments for grouped data, Measures of skewness based on quartiles and moments, kurtosis based on moments with real life examples. Unit-II Probability: Basic concepts of probability, deterministic and random experiments, trial, outcome, sample space, event, operations of events, mutually exclusive and exhaustive events, equally likely and favorable events with examp