statsdept

 Computer Lab - Practical Question Bank FACULTY OF COMMERCE, OSMANIA UNIVERSITY ------------------------------------------------------------------------------------------------------------ II B.Com (Business Analytics) CBCS Semester – IV (W.E.F.2022-23) Forecasting & Predictive Analytics - Paper: DSC - 403 Time: 60 Minutes                                                   Record : 10 Viva-voice : 10 Skill Test : 15 Total Marks : 35 Forecasting & Predictive Analytics  (Click here for Question Bank)

Computer Lab - Practical Question Bank FACULTY OF COMMERCE, OSMANIA UNIVERSITY ------------------------------------------------------------------------------------------------------------ I B.Com (Business Analytics) CBCS Semester - II (W.E.F.2021-22) Data Analytics Essentials - Paper: DSC - 203 Time: 60 Minutes                                                                                          Record : 10                                                                                                                              Viva-voce : 10                                                                                                                               Skill Test : 15                                                                                                                              Total Marks : 35 Data Analytics Essentials  (Click here for Question Bank)

 B.A/B.Sc. III Year V Semester (CBCS) : Statistics Syllabus (With Mathematics Combination) (Examination at the end of Semester - V) Paper – VI - GE : Basic Statistics [4 HPW :: 4 Credits :: 100 Marks] UNIT I Introduction: Definition and scope of Statistics, concepts of statistical population and sample. Data: quantitative and qualitative, attributes, variables, scales of measurement - nominal, ordinal, interval and ratio. Presentation: tabular and graphic, including histogram and ogives. UNIT II Measures of Central Tendency: mathematical and positional. Measures of Dispersion: range, quartile deviation, mean deviation, standard deviation, coefficient of variation, moments, skewness and kurtosis. UNIT III Bivariate data: Definition, scatter diagram, simple, partial and multiple correlation (3 variables only), rank correlation. Simple linear regression, principle of least squares and fitting of polynomials and exponential curves. UNIT IV Theory of attributes, consistency of data, indepen

 

  GE – Basic Statistics (Important Questions) UNIT – I 1.Define Statistics. Explain scope of statistics. 2.Explain measurement of scales.  3.What is meant by tabulation? Explain various kinds of tables. 4.Define the following with example Population, Sample, Variable, Attributes 5.Draw Ogive curve for the following data. Marks 0-10 10-20 20-30 30-40 40-50 50-60 60-70 70-80 80-90 90-100 No. of Students 8 12 22 35 40 60 52 40 30 5           6.What is the difference between qualitative and quantitative data? Explain with example.   UNIT - II 1.Define central tendency. Explain measures of central tendency with merits and demerits. 2.What is meant by dispersion? Explain measures of dispersion with merits and demerits. 3.Obtain Mean, Median and Mode from the following data

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