Course Details
Subject {L-T-P / C} : MA4272 : Statistics Laboratory { 1-0-2 / 2}
Subject Nature : Practical
Coordinator : Prof. Manas Ranjan Tripathy
Syllabus
Generation of random numbers, Computation of mean, variance, standard deviation, etc., for the datasets generating random variables, such as uniform, normal, exponential, Weibull, and gamma, using the C- program computation of mean, variance, moments, skewness, kurtosis for all these distributions, numerically after generating random variables. Computation of maximum likelihood estimator and method of moment estimator for the unknown parameters involved in a distribution, Computation of confidence intervals for the mean and variance of normal random variables, Computation of regression line and correlation coefficient using the datasets, Goodness of fit chi-square test for fitting distribution.
Course Objectives
- Students will learn the method of gerating data using random variables.
- The students will be able to compute the various moments such as mean, variance, standard deviation, skewness, and kurtosis using the generated datasets.
- The students will learn the procedure for fitting a regression line for a data pair and use it for prediction.
- The students will compute the point estimation and confidence intervals for the unknown parameters involved in a distribution.
Course Outcomes
The students will be equipped with some numerical techniques that can be used to solve some statistical problems. Data analysis is one of the major problems nowadays. It will help the students to get a better job in industry or any other sector where data analysis is essential.
Essential Reading
- Averill Law (Author), W. David Kelton, Simulation Modeling and Analysis, McGraw-Hill Education
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Supplementary Reading
- Averill Law (Author), W. David Kelton (Author), Simulation Modeling and Analysis, McGraw-Hill Education
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