Course Details

Subject {L-T-P / C} : SM6572 : Statistics Laboratory { 0-0-2 / 2}

Subject Nature : Practical

Coordinator : Dr. Arvind Kumar

Syllabus

Unit 1. Introduction to Statistics and Data Collection: Business Statistics, Collection of Data, Populations and Samples, Nature of Statistical Data and Measurement Levels, Scales of Measurement, Types of Statistical Data. (Lecture Hours - 3)

Unit 2. Univariate Analysis: (i) Measures of Central Tendency: Introduction, Central Tendency, Requisites of a Good Average, Measures of Central Tendency (ii) Measures of Variation: Variability and Decision Making, Absolute and Relative Variation, Measures of Variation (iii) Measures of Symmetry and tailedness: Skewness, Difference Between Dispersion and Skewness, Kurtosis (Lecture Hours - 6)

Unit 3. Bivariate Analysis: Correlation, Simple Regression (Lecture Hours - 3)

Unit 4. Multivariate Analysis: Exploratory Factor Analysis, Cluster Analysis, Multiple Regression, Discriminant Analysis, Logistic Regression, Perceptual Mapping, Correspondence Analysis, Conjoint Analysis, Multivariate Analysis of Variance and Covariance (Lecture Hours - 9)

Unit 5. Statistical Quality Control: Introduction, Control Charts, Control Charts for Variables, Control Charts for Attributes, Acceptance Sampling (Lecture Hours - 6)

Unit 6. Probability: Introduction, Marginal Probability, Joint Probability, Conditional Probability, Bayes’ Theorem (Lecture Hours - 3)

Course Objectives

Course Outcomes

After completion of this course, the pupils shall be able to – <br />(i) Describe all the key concepts of Statistical analysis with ease <br />(ii) Organize, manage and present data independently <br />(iii) Analyse statistical data using measures of central tendency, dispersion and location <br />(iv) Calculate coefficient of correlation independently <br />(v) Build the simple linear regression Model without the help of Excel and SPSS <br />(vi) Calculate Coefficient of Determination (R2) without the help of Excel and SPSS <br />(vii) Build the multiple and logistics regression Model on MSExcel and SPSS <br />(viii) Calculate the utilities through Conjoint Analysis <br />(ix) Perform discriminant and correspondence analysis independently. <br />(x) Perform MANOVA independently <br />(xi) Prepare control charts with ease <br />(xii) Explain the concept of probability with ease <br />(xiii) Apply Joint Probability, Conditional Probability and Bayes’ theorem to calculate the likelihood of event(s).

Essential Reading

Supplementary Reading