__MT-330 APPLIED PROBABILITY & STATISTICS__

__CREDIT HOURS__

Theory = 2

Practical = 1

**COURSE LEARNING OUTCOMES (CLOs)**

S. No. |
CLOs |
PLO |
Taxonomy |

1 | Discuss the fundamental concepts in Probability and Statistics | PLO-1 |
Coginitive |

2 | Analyze on data & produce mathematical probabilistic models for different problems and to interpret the results | PLO-2 | Coginitive Level 4* |

3 | Perform statistical analysis on data through computer software | PLO-5 | Psychomotor Level 3* |

**COURSE CONTENT**

Introduction, types of data & variables, presentation of data, object, classifications, tabulations, frequency distribution, graphical representation, simple and multiple bar diagrams, sartorial and pie-diagram, histogram, frequency polygon, frequency curves and their types.**Statistics:**Statistics averages, median, mode, quartiles, range, moments, skew-ness and Kurtosis. Quartile deviation, mean deviation, standard deviation, variance and its coefficient. Significance in related problems.**Measure of Central Tendency & Dispersion:**Introduction, fitting of a first and second degree curve, fitting of exponential and logarithmic curves, related problems. Principle of least squares and second order statistics and time series.__Curve Fitting:__Introduction, Scatter diagrams, Correlation & its Coefficient, Regression lines, Rank Correlation & its Coefficient, Probable Error (PE), related problems.**Simple Regression & Correlation:**Introduction, Population, Parameter & Statistic, Objects of sampling, Sampling distribution of Mean, Standard errors, Sampling & Non-Sampling errors, Random Sampling, Sampling with & without replacement, Sequential Sampling, Central limit theorem with practical significance in related problems.**Sampling & Sampling Distributions:**Testing of Hypothesis: Introduction, Estimation, Types of Estimates, Confidence interval, Tests of Hypothesis, Chi-Square distribution/test, one tails & two tails tests. Application in related problems.**Statistical Inference:**Basic concepts, Permutation & Combination, Definitions of probability, Laws of probability. Conditional probability, Baye's nile. Related problems in practical significance.**Probability:**Introduction, Discrete & Continuous random variables. Random Sequences and transformations Probability distribution, Probability density function, Distribution function, Mathematical expectations, Moment Generating Function (M.G.F), Markove random walk chain related problems.**Random Variables:**Introduction, discrete probability distributions, Binomial, Poisson, Hyper geometric & Negative binomial distributions. Continuous probability distribution, Uniform, Exponential & Normal distributions & their practical significance.**Probability Distributions:**

**RECOMMENDED BOOKS**

*(01) Introduction to Statistics by Walpole*

*(02) Mathematical Statistics by Hogg and Craig*

*(03) Exploring Statistics by Larry J. Kitchens*

*For details of Taxonomy Levels **CLICK HERE!**