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UNIT-I
Descriptive Statistics and Methods for Data Science: Data Science – Statistics Introduction –
Population Vs Sample – Collection of Data – Primary and Secondary Data – Type of Variable: Dependent
and Independent Categorical and Continuous Variables – Data Visualization – Measures of Central
Tendency – Measures of Variability (Spread or Variance) – Skewness Kurtosis.
UNIT-II
Correlation and Curve Fitting: Correlation – Correlation Coefficient – Rank Correlation – Regression
Coefficients and Properties – Regression Lines – Method of Least Squares – Straight Line – Parabola
– Exponential – Power Curves.
UNIT-III
Probability and Distributions: Probability – Conditional Probability and Baye’s Theorem – Random
Variables – Discrete and Continuous Random Variables – Distribution Function – Mathematical Expectation
and Variance – Binomial, Poisson, Uniform and Normal Distributions.
UNIT-IV
Sampling Theory: Introduction – Population and Samples – Sampling Distribution of Means and Variance
(Definition only) – Central Limit Theorem (Without Proof) – Introduction to t, χ2 and F-Distributions – Point
and Interval Estimations – Maximum Error of Estimate.
UNIT-V
Tests of Hypothesis: Introduction – Hypothesis – Null and Alternative Hypothesis – Type I and Type
II Errors – Level of Significance – One-tail and Two-tail Tests – Tests Concerning One Mean and Two
Means (Large and Small Samples) – Tests on Proportions.