syllabus – SNS Courseware

23ADO201 DATA SCIENCE FUNDAMENTALS

UNIT 1 INTRODUCTION TO DATA SCIENCE

Need for data science ᎓ benefits and uses ᎓ facets of data ᎓ data science process ᎓ setting the research goal ᎓ retrieving data ᎓ cleansing, integrating, and transforming data ᎓ exploratory data analysis.

UNIT 2 DESCRIPTIVE ANALYTICS

Frequency distributions ᎓ Outliers ᎓interpreting distributions ᎓ graphs ᎓ averages – describing variability – Normal distributions ᎓ z scores ᎓correlation ᎓ scatter plots ᎓ regression ᎓ regression line᎓ multiple regression equations

UNIT 3 INFERENTIAL STATISTICS

Populations ᎓ samples ᎓ random sampling ᎓ Sampling distribution- standard error of the mean – Hypothesis testing ᎓ z-test ᎓ z-test procedure ᎓decision rule ᎓ calculations ᎓ decisions ᎓ interpretations – one-tailed and two-tailed tests.

UNIT 4 ANALYSIS OF VARIANCE

t-test for one sample ᎓ sampling distribution of t ᎓ t-test procedure ᎓ t-test for two independent samples ᎓ p-value ᎓ statistical significance ᎓ t-test for two related samples.

UNIT 5 PREDICTIVE ANALYTICS

Linear least squares ᎓ implementation ᎓ goodness of fit ᎓ testing a linear model ᎓ weighted resampling

Reference Book:

1. Allen B. Downey, ᎜Think Stats: Exploratory Data Analysis in Python᎝, Green Tea Press, 2014. 2. Sanjeev J. Wagh, Manisha S. Bhende, Anuradha D. Thakare, ᎜Fundamentals of Data Science᎝, CRC Press, 2022. 3. Chirag Shah, ᎜A Hands-On Introduction to Data Science᎝, Cambridge University Press, 2020. 4. Vineet Raina, Srinath Krishnamurthy, ᎜Building an Effective Data Science Practice: A Framework to Bootstrap and Manage a Successful Data Science Practice᎝, Apress, 2021.

Text Book:

1. David Cielen, Arno D. B. Meysman, and Mohamed Ali, ᎜Introducing Data Science᎝, Manning Publications, 2016. (first two chapters for Unit I). 2. Robert S. Witte and John S. Witte, ᎜Statistics᎝, Eleventh Edition, Wiley Publications, 2017. 3. Jake VanderPlas, ᎜Python Data Science Handbook᎝, O᎙Reilly, 2016