STUDY NOTES MATERIALS MBA STATISTICS TOPIC WISE ANALYSIS 1000+ Numericals Solved (SPIRAL)

WRITTEN ACCORDING TO SYLLABUS OF STATISTICS OF ALL OVER INDIA / ALL UNIVERSITIES COVERING ALL TOPICS OF STATISTICS COURSES IN MBA WITH MODEL ANSWERS AND MCQ QUESTIONS AS WELL. COMPLETE ANALYSIS OF TOPICS WITH 2000+ SOLVED EXAMPLES TOPICS COVERED ARE AS FOLLOWS 1. INTRODUCTION: STATISTICS AS A SUBJECT; FUNCTIONS, IMPORTANCE AND LIMITATIONS OF STATISTICS; PLANNING AND EXECUTION OF A STATISTICAL INVESTIGATION; CENSUS AND SAMPLE INVESTIGATION; 2. COLLECTION, EDITING AND PRESENTATION OF DATA: PRIMARY DATA AND SECONDARY DATA; METHODS OF COLLECTION; SCRUTINY OF DATA. PRESENTATION OF DATA: TEXTUAL AND TABULAR PRESENTATIONS; CONSTRUCTION OF A TABLE AND DIAGRAMMATIC REPRESENTATION OF DATA: 3. FREQUENCY DISTRIBUTIONS: ATTRIBUTE AND VARIABLE; FREQUENCY DISTRIBUTION OF AN ATTRIBUTE; DISCRETE AND CONTINUOUS VARIABLES; FREQUENCY DISTRIBUTIONS OF DISCRETE AND CONTINUOUS VARIABLES; BIVARIATE AND MULTIVARIATE FREQUENCY DISTRIBUTIONS. DIAGRAMMATIC REPRESENTATION OF A FREQUENCY DISTRIBUTION: CASE OF AN ATTRIBUTE; CASE OF A DISCRETE VARIABLE 4. MEASURES OF CENTRAL TENDENCY: DEFINITION AND UTILITY; CHARACTERISTICS OF A GOOD AVERAGE; DIFFERENT MEASURES OF AVERAGE; ARITHMETIC MEAN; MEDIAN; OTHER POSITIONAL MEASURES – QUARTILES, DECILES, PERCENTILES; MODE; 5. MEASURES OF DISPERSION: MEANING AND OBJECTIVE OF DISPERSION; CHARACTERISTICS OF A GOOD MEASURE OF DISPERSION; DIFFERENT MEASURES OF DISPERSION – RANGE, QUARTILE DEVIATION, MEAN DEVIATION, MEAN ABSOLUTE DEVIATION, STANDARD DEVIATION; COMPARISON OF THE DIFFERENT MEASURES OF DISPERSION. 6. MOMENTS, SKEWNESS AND KURTOSIS: MOMENTS; COEFFICIENTS BASED ON MOMENTS; SHEPPARD’S CORRECTION; SKEWNESS; MEASURES OF SKEWNESS; KURTOSIS AND ITS MEASURES. 7. CORRELATION AND REGRESSION: ANALYSIS OF BIVARIATE DATA. CORRELATION ANALYSIS – MEANING OF CORRELATION; SCATTER DIAGRAM; KARL PEARSON’S COEFFICIENT OF LINEAR CORRELATION; CALCULATION OF THE CORRELATION COEFFICIENT FROM GROUPED DATA; PROPERTIES OF THE CORRELATION COEFFICIENT; ADVANTAGES AND LIMITATIONS OF THE COEFFICIENT OF CORRELATION; IDEA OF RANK CORRELATION; SPEARMAN’S RANK CORRELATION COEFFICIENT. 8. INDEX NUMBERS: DEFINITION, CHARACTERISTIC AND USES OF INDEX NUMBERS; METHODS OF CONSTRUCTING PRICE AND QUANTITY INDICES (SIMPLE AND AGGREGATE); VALUE INDEX; COMPARISON OF LASPEYRES’ AND PAASCHE’S INDEX NUMBERS; CHAIN-BASE INDEX NUMBERS; BASE SHIFTING, SPLICING AND DEFLATING; 9. ANALYSIS OF TIME SERIES: OBJECTIVE OF TIME SERIES ANALYSIS; CAUSES OF VARIATIONS IN TIME SERIES DATA; COMPONENTS OF A TIME SERIES; DECOMPOSITION – ADDITIVE AND MULTIPLICATIVE MODELS; DETERMINATION OF TREND – MOVING AVERAGES METHOD AND METHOD OF LEAST SQUARES; 10. THEORY OF PROBABILITY: PROBABILITY AS A CONCEPT; BASIC PROBABILITY RULES; TREE DIAGRAMS; CONDITIONAL PROBABILITY; MUTUALLY EXCLUSIVE EVENTS AND INDEPENDENT EVENTS; BAYES’ THEOREM 11. PROBABILITY DISTRIBUTION OF A RANDOM VARIABLE: DISCRETE AND CONTINUOUS RANDOM VARIABLES; EXPECTATION VALUE; MEAN AND VARIANCE OF A RANDOM VARIABLE. 12. THEORETICAL PROBABILITY DISTRIBUTIONS: PROBABILITY MASS FUNCTION AND DENSITY FUNCTION; DISCRETE DISTRIBUTIONS – THE BINOMIAL DISTRIBUTION AND ITS PROPERTIES; IDEA OF GEOMETRICAL AND HYPERGEOMETRIC DISTRIBUTIONS. THE POISSON DISTRIBUTION AND ITS PROPERTIES; FITTING A BINOMIAL OR POISON DISTRIBUTION TO AN OBSERVED DISTRIBUTION. CONTINUOUS DISTRIBUTIONS 13. SAMPLING AND SAMPLING DISTRIBUTIONS: SAMPLING VERSUS COMPLETE ENUMERATION; RANDOM AND NONRANDOM SAMPLING; DIFFERENT TYPES OF RANDOM SAMPLING; SAMPLE STATISTIC AND POPULATION PARAMETER; PRACTICAL METHODS OF DRAWING A RANDOM SAMPLE. SAMPLING DISTRIBUTIONS – STANDARD ERROR; SAMPLING DISTRIBUTION OF THE SAMPLE MEAN AND THE SAMPLE PROPORTION. 14. ESTIMATION: POINT AND INTERVAL ESTIMATION; CRITERIA OF A GOOD ESTIMATOR; METHODS OF POINT ESTIMATION – THE METHOD OF MAXIMUM LIKELIHOOD AND THE METHOD OF MOMENTS; INTERVAL ESTIMATES – INTERVAL ESTIMATES AND CONFIDENCE INTERVALS; 15. HYPOTHESES TESTING: CONCEPTS BASIC TO THE HYPOTHESIS TESTING PROCEDURE; STEPS IN HYPOTHESIS TESTING; TYPE I AND TYPE II ERRORS; TWO-TAILED AND ONE-TAILED TESTS OF HYPOTHESES. HYPOTHESIS TESTING OF MEANS WHEN THE POPULATION STANDARD DEVIATION IS KNOWN / NOT KNOWN; POWER OF A HYPOTHESIS TEST; 16. CHI-SQUARE AND ANALYSIS OF VARIANCE: CHI-SQUARE AS A TEST OF INDEPENDENCE AND AS A TEST OF GOODNESS OF FIT. ANALYSIS OF VARIANCE.