Course studying students under JNTUA, I year II semester

summarize the basic concepts of data science and its importance in engineering  ● analyze the data quantitatively or categorically , measure of averages, variability  ● adopt correlation methods and principle of least squares, regression analysis 

define the terms trial, events, sample space, probability, and laws of probability  ● make use of probabilities of events in finite sample spaces from experiments  ● apply Baye’s theorem to real time problems  ● explain the notion of random variable, distribution functions and expected value

apply Binomial and Poisson distributions for real data to compute probabilities, theoretical frequencies  ● interpret the properties of normal distribution and its applications 

explain the concept of estimation, interval estimation and confidence intervals  ● apply the concept of hypothesis testing for large samples 

apply the concept of testing hypothesis for small samples to draw the inferences  ● estimate the goodness of fit 

make use of the concepts of probability and their applications  ● apply discrete and continuous probability distributions  ● classify the concepts of data science and its importance  ● interpret the association of characteristics and through correlation and regression tools  ● design the components of a classical hypothesis test  ● infer the statistical inferential methods based on small and large sampling tests