S. P. Mandali’s
AC/II(20-21).2.RUA14S. P. Mandali’sRamnarain Ruia Autonomous College(Affiliated to University of Mumbai)Syllabus forProgram: B. A.Program Code: (STATISTICS) RUASTA(Credit Based Semester and GradingSystem for academic year 2020–2021)
RAMNARAIN RUIA AUTONOMOUS COLLEGE, SYLLABUS FOR STATISTICS 2020-2021PROGRAM OUTCOMESS. P. Mandali’s Ramnarain Ruia Autonomous College has adopted the Outcome BasedEducation model to make its science graduates globally competent and capable ofadvancing in their careers. The Bachelors Program in Science also encourages students toreflect on the broader purpose of their education.POPO DescriptionA student completing Bachelor’s Degree in Arts program will be able to:PO 1Demonstrate understanding and skills of application of knowledge of historicaland contemporary issues in the social and linguistic settings with atransdisciplinary perspective to make an informed judgement.PO 2Analyse and evaluate theories of individual and social behaviour in the familiarcontexts and extrapolate to unfamiliar contexts in order to resolvecontemporary issues.PO 3Effectively and ethically use concepts, vocabularies, methods and moderntechnologies in human sciences to make meaningful contribution in creation ofinformation and its effective disseminationPO 4Explore critical issues, ideas, phenomena and debates to define problems or toformulate hypotheses; as well as analyse evidences to formulate an opinion,identify strategies, evaluate outcomes, draw conclusions and/or develop andimplement solutions.PO 5Demonstrate oral and written proficiency to analyse and synthesise informationand apply a set of cognitive, affective, and behavioral skills to work individuallyand with diverse groups to foster personal growth and better appreciate thediverse social world in which we live.PO 6Develop a clear understanding of social institutional structures, systems,procedures, and policies existing across cultures, and interpret, compare andcontrast ideas in diverse social- cultural contexts, to engage reasonably withdiverse groups.1
RAMNARAIN RUIA AUTONOMOUS COLLEGE, SYLLABUS FOR STATISTICS 2020-2021PO 7React thoughtfully with emotional and moral competence to forms of expressivedirect action and apply social strategies toward eradicating threats to ademocratic society and a healthy planet.PO 8Articulate and apply values, principles, and ideals to the current societalchallenges by integrating management and leadership skills to enhance thequality of life in the civic community through actions that enrich individual livesand benefit the community.PO 9Recognize and appreciate the diversity of human experience and thought, andapply intellect and creativity to contemporary scenario, to promote individualgrowth by practicing lifelong learning.PROGRAM SPECIFIC OUTCOMESPSODescriptionA student completing Bachelor’s Degree in Arts program inthe subject of Statistics will be able to:PSO 1Understand, condense, visualize, analyze and interpret the datacollected in daily walk of life.PSO 2Understand the data generated in various scenarios of scientific,industrial, or social problems.PSO 3Pursue their higher education programs leading to post-graduateor doctoral degrees.PSO 4Enhance knowledge of Statistical tools.PSO 5Enhance the theoretical rigor with technical skills which preparethem to become globally competitive to enter into a promisingprofessional life after graduation.2
RAMNARAIN RUIA AUTONOMOUS COLLEGE, SYLLABUS FOR STATISTICS 2020-2021Make a pathway to a range of traditional avenues in AcademiaPSO 6and Industry , Govt. Service, IAS, Indian Statistical/ EconomicServices, Industries, Commerce, Investment Banking, Banksand Insurance Sectors, CSO and NSSO, ResearchPersonnel/Investigator in Govt. organizations such as NCAER,IAMR, ICMR, Statistical and Economic Bureau & various PSUs.,Market Research, Actuarial Sciences, Biostatistics, Demographyetc.Seek employment in different sectors like Stock trading, Sports,PSO 7Politics, Business, Financial services and Media Industry.PROGRAM OUTLINEYEARSEMCOURSECOURSE TITLECREDITSCODEFYBAIRUASTA101DESCRIPTIVE STATISTICS - I2FYBAIRUASTAP101Practical based on RUASTA1011FYBAIIRUASTA201DESCRIPTIVE STATISTICS - II2FYBAIIRUASTAP201Practical based on RUASTA2011SYBAIIIRUASTA301STATISTICAL METHODS - I2SYBAIIIRUASTA302OPERATIONS RESEARCH2SYBAIIIRUASTAP301Practical based on RUASTA301 &2RUASTA302SYBAIVRUASTA401STATISTICAL METHODS – II2SYBAIVRUASTA402PROJECT MANAGEMENT AND2INDUSTRIAL STATISTICS3
RAMNARAIN RUIA AUTONOMOUS COLLEGE, SYLLABUS FOR STATISTICS 2020-2021SYBAIVRUASTAP401Practical based on RUASTA401 &2RUASTA402TYBAVRUASTA501PROBABILITY DISTRIBUTIONS3TYBAVRUASTA502THEORY OF SAMPLING3TYBAVRUASTA503ELEMENTS OF ACTUARIAL2.5SCIENCETYBAVRUASTAP501Practical based on RUASTA501,3RUASTA502 & RUASTA503TYBAVIRUASTA601PROBABILITY AND SAMPLING3DISTRIBUTIONSTYBAVIRUASTA602ANALYSIS OF VARIANCE &3DESIGN OF EXPERIMENTSTYBAVIRUASTA603APPLIED STATISTICS2.5TYBAVIRUASTAP601Practical based on RUASTA601,3RUASTA602 & RUASTA6034
RAMNARAIN RUIA AUTONOMOUS COLLEGE, SYLLABUS FOR STATISTICS 2020-2021Course Code: RUASTA101Course Title: DESCRIPTIVE STATISTICS - IAcademic year 2020-21COURSE OUTCOMES:COURSEOUTCOMECO 1CO 2CO 3CO 4CO 5CO 6DESCRIPTIONA student completing this course will be able to:Distinguish between different types of scales. Compare the differenttypes of data and describe the various methods of data collection.Compute Yule’s coefficient of association Q and Yule’s coefficient ofColligation Y and associate two attributes, and relate Q and Y.Construct Univariate and Bivariate frequency distribution of discrete,continuous variables and Cumulative frequency distribution. DrawGraphs and Diagrams: Histogram, Polygon/curve, Ogives. Heat Map,Tree map.Describe the need of measures of central tendency, Explain thevarious measures of central tendencies. Relate mean, median andmode. Justify merits and demerits of using different measures.Compute and comprehend the measures of dispersion. CompareAbsolute and Relative measures of dispersion.Relate raw moments and central moments. Understand Skewnessand Kurtosis of data. Identify the outliers.DETAILED SYLLABUSCourseCode/ UnitRUASTA101UnitCourse/ Unit TitleUnit Types of Data and Data Condensation: GlobalSuccessstoriesofIStatistics/Analytics in various fields. Concept of Population and Sample. Finite,Infinite Population, Notion of SRS, SRSWORand SRSWR Different types of scales: Nominal, Ordinal,Interval and Ratio. Methods of Data Collection: i) Primary data:concept of a Questionnaire and a Schedule, ii)Secondary Data5Credits/Lectures15Lectures
RAMNARAIN RUIA AUTONOMOUS COLLEGE, SYLLABUS FOR STATISTICS 2020-2021 RUASTA101RUASTA101Types of data: Qualitative and Quantitative Data;Time Series Data and Cross Section Data,Discrete and Continuous Data Tabulation Dichotomous classification- for two and threeattributes, Verification for consistency Association of attributes: Yule’s coefficient ofassociation Q. Yule’s coefficient of Colligation Y,Relation between Q and Y (with proof). Univariate frequency distribution of discrete andcontinuous variables. Cumulative frequencydistribution Data Visualization: Graphs and Diagrams:Histogram, Polygon/curve, Ogives. Heat Map,Tree map. Bivariate Frequency Distribution of discrete andcontinuous variablesUnit Measures of central tendency Concept of central tendency of data,IIRequirements of good measures of centraltendency. Location parameters: Median, Quartiles,Deciles, and Percentiles Mathematical averages Arithmetic mean(Simple, weighted mean, combined mean),Geometric mean, Harmonic mean, Mode,Trimmed mean. Empirical relation between mean, median andmode. Merits and demerits of using different measures& their applicability.Unit Measures of Dispersion, Skewness & Kurtosis Concept of dispersion, Requirements of goodIIImeasure Absolute and Relative measures of dispersion:Range, Quartile Deviation, Inter Quartile Range,Mean absolute deviation, Standard deviation. Variance and Combined variance, raw momentsand central moments and relations betweenthem. Their properties Concept of Skewness and Kurtosis: Measures ofSkewness: Karl Pearson’s, Bowley’s andCoefficient of skewness based on moments.Measure of Kurtosis. Absolute and relativemeasures of skewness.Box Plot: Outliers615Lectures15Lectures
RAMNARAIN RUIA AUTONOMOUS COLLEGE, SYLLABUS FOR STATISTICS 2020-2021Distribution of topics for PracticalsCourse Code RUASTAP101Sr. No.1234567Practicals based on courseTabulationClassification of DataAttributesDiagrammatic representationMeasures of central tendencyMeasures of dispersionPractical using Exceli) Classification of Data and Diagrammatic representationii) Measures of central tendencyiii) Measures of dispersionReferences:1. Medhi J.: “Statistical Methods, An Introductory Text”, Second Edition, New AgeInternational Ltd.2. Agarwal B.L.: “Basic Statistics”, New Age International Ltd.3. Spiegel M.R.: “Theory and Problems of Statistics”, Schaum’s Publications series.Tata McGraw-Hill.4. Kothari C.R.: “Research Methodology”, Wiley Eastern Limited.5. David S.: “Elementary Probability”, Cambridge University Press.6. Hoel P.G.: “Introduction to Mathematical Statistics”, Asia Publishing House.7. Hogg R.V. and Tannis E.P.: “Probability and Statistical Inference”. McMillanPublishing Co. Inc.8. Pitan Jim: “Probability”, Narosa Publishing House.9. Goon A.M., Gupta M.K., Dasgupta B.: “Fundamentals of Statistics”, Volume II: TheWorld Press Private Limited, Calcutta.10. Gupta S.C., Kapoor V.K.: “Fundamentals of Mathematical Statistics”, Sultan Chand&Sons11. Gupta S.C., Kapoor V.K.: “Fundamentals of Applied Statistics”, Sultan Chand &Sons7
RAMNARAIN RUIA AUTONOMOUS COLLEGE, SYLLABUS FOR STATISTICS 2020-2021Modality of AssessmentTheory Examination Pattern:A) Internal Assessment- 40%- 40 MarksSr NoEvaluation typeMarks1Class Test/ Project / Assignment / Presentation202Class Test/ Project / Assignment / Presentation20TOTAL40B) External Examination- 60%- 60 MarksSemester End Theory Examination:1. Duration - These examinations shall be of two hours duration.2. Theory question paper pattern:Paper Pattern:QuestionOptionsMarksA1B or C20Unit I20Unit II20Unit IIIA2B or CA3B or CQuestions Based on60TOTALPractical Examination Pattern:A) Internal Examination: 40%- 40 MarksMarksParticularsJournal5Assignments using Statistical Software15Total208
RAMNARAIN RUIA AUTONOMOUS COLLEGE, SYLLABUS FOR STATISTICS 2020-2021B) External Examination: 60%- 60 MarksSemester End Practical Examination:Duration - These examinations shall be of one and half hour duration.ParticularsPaper30Exam (There shall be Three COMPULSORY Questions of 10marks each with internal choice)Total30Overall Examination & Marks Distribution PatternSemester Practicals203050Course Code: RUASTA201Course Title: DESCRIPTIVE STATISTICS - IIAcademic year 2020-21COURSE OUTCOMES:COURSEOUTCOMECO 1DESCRIPTIONA student completing this course will be able to:Compute the numerical measures to identify the direction and strength oflinear relationship between two variables using. Also, list their properties.CO 2Build a simple linear regression model and interpret regression coefficientsand coefficient of determination.CO 3CO 4Calculate and interpret various measures of associations between twoattributes.Identify various components of time series. Apply the appropriate methodsto evaluate and eliminate these components.CO 5Comprehend the concept and construct various index numbers.CO 6Use the basic mathematical operators in R for different data types. Applydifferent data management techniques and data visualisation.9
RAMNARAIN RUIA AUTONOMOUS COLLEGE, SYLLABUS FOR STATISTICS 2020-2021DETAILED SYLLABUSCourseCode/ UnitRUASTA201RUASTA201UnitCourse/ Unit TitleCredits/LecturesUNIT Correlation, Simple linear Regression Analysis15and Fitting of curvesILECTURES Karl Pearson’s Product moment correlationcoefficient and its properties. Spearman’s Rank correlation. (With and withoutties) Concept of Simple linear regression. Principleof least squares. Fitting a straight line bymethod of least squares (Linear in Parameters) Relationship between regression coefficientsand correlation coefficient, cause and effectrelationship, Spurious correlation. Concept and use of coefficient of determination2(R ). Measures of association with the help of Tau A,Tau B, Tau C, Gamma and Lambda, Somer’s d Fitting of curves reducible to linear form bytransformation.Unit Time Series and Index numbers15 Definition of time series. Components of timeIILECTURESseries. Models of time series. Estimation of trend by: (i) Freehand CurveMethod (ii) Method of Semi Average (iii) Methodof Moving Average (iv) Method of Least Squares(Linear Trend only) Estimation of seasonal component by (i) Methodof Simple Average (ii) Ratio to Moving Average(iii) Ratio to Trend Method Simple exponential smoothing Stationary Time seriesIndex numbers: Index numbers as comparative tool. Stages in theconstruction of Price Index Numbers. Measures of Simple and Composite IndexNumbers. Laspeyre’s, Paasche’s, MarshalEdgeworth’s, Dobisch & Bowley’s and Fisher’sIndex Numbers formula Quantity Index Numbers and Value IndexNumbers Time reversal test, Factor reversal test,Circular test Fixed base Index Numbers, Chain base IndexNumbers. Base shifting, splicing and deflating. Cost of Living Index Number. Concept of RealIncome.10
RAMNARAIN RUIA AUTONOMOUS COLLEGE, SYLLABUS FOR STATISTICS 2020-2021RUASTA201UNIT Fundamentals of R:15 Introduction to R, features of R, installation of R, LECTURESIIIStarting and ending R session, getting help in R, Value assigning to variables, Basic Operations: , -, *, , , sqrt, Numerical functions : log 10,log , sort, max, unique, range, length, var, prod,sum, summary, dim, sort, five num etc. Data Types: Vector, list, matrices, array anddata frame, Variable Type: logical, numeric,integer, complex, character and factor Data Manipulation: Selecting random N rows,removing, duplicate row(s), dropping avariable(s), Renaming variable(s), sub settingdata, creating a new variable(s), selecting ofrandom fraction of row(s), appending of row(s)and column(s), simulation of variables. Data Processing: Data import and export,setting working directory, checking structure ofData: Str(), Class(), Changing type of variable(for eg as.factor, as.numeric) Data Visualisation using ggplot: Simple bardiagram, subdivided bar diagram, multiple bardiagram pie diagram, Box plot for one and morevariables, histogram, frequency polygon, scatterplot. Visualizing relationship using Bubble chart,Scatter Diagram.Distribution of topics for PracticalsCourse Code RUASTAP201Sr. No.123456Practicals based on courseCorrelation analysisRegression analysisFitting of curveTime seriesIndex Numbers.Practical using Ri) Measures of Central Tendencyii) Measures of Dispersioniii) Diagrams and Graphsiv) Correlation analysisv) Regression analysisvi) Fitting of curveREFERENCES:1. Medhi J.:“Statistical Methods, An Introductory Text”, Second Edition, New AgeInternational Ltd.2. Agarwal B.L.:“Basic Statistics”, New Age International Ltd.11
RAMNARAIN RUIA AUTONOMOUS COLLEGE, SYLLABUS FOR STATISTICS 2020-20213. Spiegel M.R.:“Theory and Problems of Statistics”, Schaum’s Publications series.Tata McGraw-Hill.4. Kothari C.R.:“Research Methodology”, Wiley Eastern Limited.5. David S.:“Elementary Probability”, Cambridge University Press.6. Hoel P.G.:“Introduction to Mathematical Statistics”, Asia Publishing House.7. Hogg R.V. and Tannis E.P.:“Probability and Statistical Inference”. McMillanPublishing Co. Inc.8. Pitan Jim:“Probability”, Narosa Publishing House.9. Goon A.M., Gupta M.K., Dasgupta B.:“Fundamentals of Statistics”, Volume II: TheWorld Press Private Limited, Calcutta.10. Gupta S.C., Kapoor V.K.: “Fundamentals of Mathematical Statistics”, Sultan Chand&Sons11. Gupta S.C., Kapoor V.K.: “Fundamentals of Applied Statistics”, Sultan Chand &SonsModality of AssessmentTheory Examination Pattern:A) Internal Assessment- 40%- 40 MarksSr NoEvaluation typeMarks1Class Test/ Project / Assignment / Presentation202Class Test/ Project / Assignment / Presentation20TOTAL40B) External Examination- 60%- 60 MarksSemester End Theory Examination:1. Duration - These examinations shall be of two hours duration.2. Theory question paper pattern:Paper Pattern:Question1OptionsAB or C2Unit I20Unit II20Unit IIIAB or CQuestions Based on20AB or C3Marks60TOTAL12
RAMNARAIN RUIA AUTONOMOUS COLLEGE, SYLLABUS FOR STATISTICS 2020-2021Practical Examination Pattern:A) Internal Examination: 40%- 40 MarksMarksParticularsJournal5Projects based on primary / secondary data15Total20B) External Examination: 60%- 60 MarksSemester End Practical Examination:Duration - These examinations shall be of one and half hour duration.ParticularsPaper30Exam (There shall be Three COMPULSORY Questions of 10marks each with internal choice)Total30Overall Examination & Marks Distribution PatternSemester 0Practicals20305013
RAMNARAIN RUIA AUTONOMOUS COLLEGE, SYLLABUS FOR STATISTICS 2020-2021Course Code: RUASTA301Course Title: STATISTICAL METHODS- IAcademic year 2020-21COURSE OUTCOMES:COURSEOUTCOMEDESCRIPTIONA student completing this course will be able to:CO 1Differentiate between random and non-random experimentsCO 2Compute the probabilities of eventsCO 3Understand the concept of a random variable, its probability distribution ofa random variable (one or two) and its propertiesCO 4Apply standard discrete probability distributions based on real lifesituationsDETAILED SYLLABUSCourseCode/ UnitRUASTA301RUASTA301UnitCourse/ Unit TitleUnit Elementary Probability TheoryI Trial, random experiment, sample point andsample space. Definition of an event, Operation of events,mutually exclusive and exhaustive events. Classical (Mathematical) and Empiricaldefinitions of Probability and their properties. Theorems on Addition and Multiplication ofprobabilities Independence of events, Pair-wise and MutualIndependence for three events, Conditionalprobability, Bayes’ theorem and its applicationsUnit Discrete random variableII Random variable. Definition and properties ofprobability distribution and cumulativedistribution function of discrete randomvariable. Raw and Central moments and ectures
RAMNARAIN RUIA AUTONOMOUS COLLEGE, SYLLABUS FOR STATISTICS 2020-2021 RUASTA301UnitIIIConcepts of Skewness and Kurtosis and theiruses. Expectation of a random variable. Theoremson Expectation & Variance. Concept ofGenerating function, Moment Generatingfunction, Cumulant generating function,Probability generating function Joint probability mass function of two discreterandom variables. Independence of tworandom variables. Marginal and conditional distributions.Theorems on Expectation &Variance,Covariance and Coefficient of Correlation.Some Standard Discrete Distributions Degenerate (one point): Discrete c distributions derivation of theirmean and variance for all the abovedistributions. Moment Generating Function and CumulantGenerating Function of Binomial and Poissondistribution.Recurrence relationship for probabilities ofBinomial and Poisson distributions, Poissonapproximation to Binomial distribution, Binomialapproximation to hypergeometric distribution.15LecturesDistribution of topics for PracticalsCourse Code RUASTAP301(A)Sr. No.1234567Practicals based on courseProbabilityDiscrete Random VariablesBivariate Probability DistributionsBinomial DistributionPoisson DistributionHypergeometric DistributionPractical using Exceli) Binomial distributionii) Poisson distributioniii) Hypergeometric distributionReferences:1.Medhi J.: “Statistical Methods, An Introductory Text”, Second Edition, New AgeInternational Ltd.2.Agarwal B.L.: “Basic St
Politics, Business, Financial services and Media Industry. PROGRAM OUTLINE YEAR SEM COURSE CODE . RUASTA101 1 FYBA II RUASTA201 DESCRIPTIVE STATISTICS - II 2 FYBA II RUASTAP201 Practical based on RUASTA201 1 SYBA III RUASTA301 STATISTICAL METHODS - I 2 SYBA III RUASTA302 OPERATIONS RESEARCH 2 SYBA
Om Shri Ganeshaya Namah:: ஓ ¼கணபதி ைண NEW JERSEY AYYAPPA BHAKTHA MANDALI நி ெஜ «சி ஐய ப பtத மzடலி BHAJAN BOOK பஜைன {தக
Independent Personal Pronouns Personal Pronouns in Hebrew Person, Gender, Number Singular Person, Gender, Number Plural 3ms (he, it) א ִוה 3mp (they) Sֵה ,הַָּ֫ ֵה 3fs (she, it) א O ה 3fp (they) Uֵה , הַָּ֫ ֵה 2ms (you) הָּ תַא2mp (you all) Sֶּ תַא 2fs (you) ְ תַא 2fp (you
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messages that our ancestors have with respect to Gayatri mantra and Sandhya Vandanam . Therefore, while compiling various ideas I have quoted generously from . Kannada by His Holiness Jagadguru Sri Abhinava Vidya Teertha Maha Swamigal of . Taitrya Aranyaka of Yajur Veda is a hymn to the Sun God, which is recited with fervor even today (also .
Syllabus for: S.Y. B.A. English (Ancillary) Program: B.A. Course: American Literature Course Code: RUAENG302 & RUAENG402 (Choice Based Credit System (CBCS) with effect from academic year 2020- 21 ) SEMESTER III American Literat
M. H. MEHTA SCIENCE COLLEGE, PALGHAR GOAL Higher Education To All MISSION . Botany (M.Sc.) (By Papers) - 60 17 Master of Science - Physics (M.Sc.) (By Papers) - 60 . Mr. Naman Pandey Information T echnology TCS 23] Mr. Siddhesh P atil Life Sciences Infigo EyeC
Swamiye Saranam Ayyappa Samastha Jana Mandali ki Jai 4. Thodayamangalam As a musical composition, Thodaya Mangalam is a set of songs, composed by saints like Sri Badhradri Ramadasa Swami, Sri Annamacharya, and Sri Vijayagopala Swamigal and compiled like a garland by Marudhanallur Sathguru Swamigal.
Marxism is a highly complex subject, and that sector of it known as Marxist literary criticism is no less so. It would therefore be impossible in this short study to do more than broach a few basic issues and raise some fundamental questions. (The book is as short as it is, incidentally, because it was originally designed for a series of brief introductory studies.) The danger with books of .
