UNIT–I: 

Data Visualization and Distributions

Data Visualization Techniques: Introduction to Statistical methods- Exploratory Data Analysis- Charts (Line, Pie, Bar); Plots (Bubble, Scatter); Maps (Heat, Dot Distribution); Diagrams (Trees and Matrices)-Principal Components Analysis.

Introduction to Data Distributions: Probability Distributions - Discrete (Binomial, Poisson), Continuous Distributions (Normal, Exponential). 

UNIT – II:

         Hypothesis Testing

Introduction to Parametric Estimation - Parametric Confidence Intervals - Choosing a Statistic - Hypothesis Testing - Parametric tests - the t-test - Applications to Hypothesis Testing - Pair wise comparisons.

UNIT-III: 

        Linear Regression and Multiple Regression

Regression: Linear Regression, Curvilinear Regression - Exponential Regression- Polynomial Regression- Power Model.

Practical Examples - The nature of the ‘relationship’ - Multiple Linear Regression - Important measurements of the regression estimate - Multiple Regression with Categorical Explanatory Variables - Inference in Multiple Regression - Variable Selection.

UNIT – IV: 

        Time Series

Time series: Significance of Time series analysis, Components of Time series, Secular trend: Graphic method, Semi-average method, Method of moving averages, Method of least squares: straight line and non-linear trends, Logarithmic methods–Exponential trends, Growth curves, Seasonal Variations: Method of simple averages, Ratio – to –trend method, Ratio - to-moving averages method, Link relative’s method. 

UNIT – V: 

         Logistic Regression

The classification Problem-Logistic Regression Setup-Interpreting the Results- Comparing Models - Classification using Logistic Regression,

     Text Books:

1.  Elizabeth Purdom,"Statistical methods for Data science" (08.05.2023)

2. K. Murugesan, P. Gurusamy“Probability,Statistics and Random Processes”, Anuradha Publications (January-2009), ISBN-10(8189638289)/ISBN-13(978-8189638283).

          References:

1.      Manoj Kumar Srivastava and NamitaSrivastava ,Statistical Inference–Testing of Hypotheses, Prentice Hall of India, 2014.

2.      Robert V Hogg, Elliot A Tannis and Dale L.Zimmerman, Probability and Statistical Inference,9thedition, Pearson publishers,2013.

3.      Chris Chatfield, “The analysis of time series an introduction,” 5th edition, Chapman &Hall/CRC.

4.      Peter J. Brockwell, Richard A.Davis, “Introduction to Time series and Forecasting,” Second

edition, Springer.