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Course : Fundamentals of Data Analytics (FDA)

Faculty : Dr.Srilakshminarayana.G Email ID: lakshminarayana@sdmimd.ac.in

Batch : 2014-16

Term : I

Credits : 3

Objectives:

The course is mainly meant to train the students in using statistical tools, which will be

ultimately used in analyzing the data sets that arise due to interaction of different business

situations. The main focus will be on solving problems via data analysis using MS-Excel.

Apart from problem solving, students will be encouraged to study selected research

articles and case studies.

Pedagogy:

The course mainly focuses on data analysis using statistical tools. Hence, the sessions

will be a blend of presentation of concepts as well as problem solving using data sets

taken from different situations. Students will be made to think in groups about problem

solving using data sets through group assignments.

Course Prerequisites:

Knowledge of MS-Excel, algebra, logic and analytical skills will be key in learning the

concepts that will be introduced during the course discussions.

Course evaluation Pattern

Component % Marks

Class participation 10

Quiz 20

Group Work 10

Mid term 30

End term 30

Total 100

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Session

No.

Session Plan

Topics

1 Importance of the course in business. Types of data and scaling with examples.

Introduction to presentation of data: Tabular and graphical.

2 Presentation of data: Tabular and Graphical (Qualitative and Quantitative)

3 Measures of Central Tendency: Mean, Median, Mode, Quartiles, and

Percentiles-Examples and Problems.

4 Measures of Variability: Mean deviation about median, Standard Deviation,

Coefficient of Variation-Examples and Problems.

5 Skewness and Kurtosis, Exploratory Data analysis-Examples and Problems.

6 Introduction to probability, basic definitions in probability theory, rules for

probability measure- Examples and Problems.

7 Conditional Probability, Independence of Events- Examples and Problems.

8 Product rules for Independent events-Examples and Problems.

9 The law of total probability and Bayes Theorem-Examples and Problems.

10 Random Variables: Discrete and Continuous-Examples and Problems.

11 Expected value, standard deviation of a random variable- Examples and

Problems. Chebyshevs Theorem and its importance.

12 Bernoulli random variable, Binomial random variable-Examples and Problems.

13 Negative Binomial distribution, Geometric distribution-Examples and Problems.

14 Hypergeometric distribution and Poisson distribution-Examples and Problems.

15 Continuous random variables, Uniform distribution and Exponential

Distribution-Examples and Problems.

16 Importance of normal distribution, properties of normal distribution, the

standard normal distribution, finding probabilities-Examples and Problems.

17 The inverse transformation, Normal approximation of Binomial and Poisson

distributions- Examples and Problems.

18 Importance of sampling in business, basic definitions. Drawing a sample using

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simple random sampling-Examples and Problems.

19 Drawing a sample using stratified random sampling-Examples and Problems.

20 Drawing a sample using systematic random sampling, cluster random sampling.

Other non-probability sampling procedures-Examples and Problems.

Recommended Text Book:

Aczel, A.D., Sounderpandian, J., Saravanan, P., and Rohit, J. (2009): Complete Business

Statistics. 7th

Edition. Tata McGraw Hill.

References:

1. Levine, D. M., Berenson, M.L., Krehbiel, T. C., and Stephan, D. F. (2011): Statistics

for Managers using MS Excel. 6th edition. Pearson.

2. Anderson, D. R., Sweeney, D.J., and Williams, T. A. (2011): Statistics for Business

and Economics.11th

Edition. Cengage.

3. Levin, R. I., and Rubin, D. S. (2000): Statistics for Management. 7th Edition.

Pearson.

4. Keller, G. (2012): Managerial Statistics. 9th Edition. South-Western Cengage.