| Sl.No | Chapter Name | MP4 Download |
|---|---|---|
| 1 | Lecture 1: Descriptive Statistics-I | Download |
| 2 | Lecture 2: Descriptive Statistics-II | Download |
| 3 | Lecture 3: Probability and Distribution | Download |
| 4 | Lecture 4: Random variable and Expectation I | Download |
| 5 | Lecture 5: Random variable and Expectation II | Download |
| 6 | Lecture 6: Random variable and Expectation III | Download |
| 7 | Lecture 7: Random variable and Expectation IV | Download |
| 8 | Lecture 8: Module: Introduction to R | Download |
| 9 | Lecture 9: R : Demos and getting help | Download |
| 10 | Lecture 10: R as calculator and plotter: Diffusivity, scaled temperatures | Download |
| 11 | Lecture 11: R as calculator and plotter: Diffraction, configurational entropy | Download |
| 12 | Lecture 12: Data in tabular form: Properties of elements | Download |
| 13 | Lecture 13: Tabular data in R: alternate methodology | Download |
| 14 | Lecture 14: Dataframe in R: Properties of elements | Download |
| 15 | Lecture 15: R libraries for plotting | Download |
| 16 | Lecture 16: Importing and plotting data | Download |
| 17 | Lecture 17: Property charts: Importing and plotting data | Download |
| 18 | Lecture 18: Introduction to R: Summary of the module | Download |
| 19 | Lecture 19: Descriptive statistics | Download |
| 20 | Lecture 20: Presenting experimental results: Data on conductivity of ETP copper | Download |
| 21 | Lecture 21: Property based reports, errors, significant digits | Download |
| 22 | Lecture 22: Dealing with distributions: Grain size data | Download |
| 23 | Lecture 23: Grain size data: Property and rank based reports | Download |
| 24 | Lecture 24: Case study: Grain size in a two phase steel | Download |
| 25 | Lecture 25: Grain size in a two phase steel: Descriptive statistics | Download |
| 26 | Lecture 26: Presenting experimental results: data with error bars | Download |
| 27 | Lecture 27: Errors and their propagation | Download |
| 28 | Lecture 28: Fitting experimental data to distributions | Download |
| 29 | Lecture 29: Combining uncertainties | Download |
| 30 | Lecture 30: Summary:Descriptive statistics | Download |
| 31 | Lecture 31: Special Random Variables I | Download |
| 32 | Lecture 32: Special Random Variables II | Download |
| 33 | Lecture 33: Special Random Variables III | Download |
| 34 | Lecture 34: Special Random Variables IV | Download |
| 35 | Lecture 35: Special Random Variables V | Download |
| 36 | Lecture 36: Probabilty Plots | Download |
| 37 | Lecture 37: Probability distributions | Download |
| 38 | Lecture 38: Properties of probability distributions | Download |
| 39 | Lecture 39: Bernoulli trials and binomial distributions | Download |
| 40 | Lecture 40: Atom probe technique and negative binomial distribution | Download |
| 41 | Lecture 41: Atom probe and hypergeometric distribution | Download |
| 42 | Lecture 42: Atom probe : analysis of error | Download |
| 43 | Lecture 43: Nucleation and Poisson distribution | Download |
| 44 | Lecture 44: Normal distribution | Download |
| 45 | Lecture 45: Normal distribution and error function | Download |
| 46 | Lecture 46: Probability scale | Download |
| 47 | Lecture 47: Sampling Distribution I | Download |
| 48 | Lecture 48: Sampling Distribution II | Download |
| 49 | Lecture 49: Sampling Distribution III | Download |
| 50 | Lecture 50: Parameter Estimation I | Download |
| 51 | Lecture 51: Parameter Estimator II | Download |
| 52 | Lecture 52: Parameter Estimator III | Download |
| 53 | Lecture 53: Parameter Estimator IV | Download |
| 54 | Lecture 54: Bayesian Estimation | Download |
| 55 | Lecture 55: Log normal distribution | Download |
| 56 | Lecture 56: Lorentz/Cauchy distribution | Download |
| 57 | Lecture 57: Lifetime and exponential distributions | Download |
| 58 | Lecture 58: Distributions from statistical mechanics | Download |
| 59 | Lecture 59: Uniform distribution and summary of probability distributions | Download |
| 60 | Lecture 60: Data processing: Introduction | Download |
| 61 | Lecture 61: Distribution function of a data series | Download |
| 62 | Lecture 62: Estimating mean and mean-square-deviation of data | Download |
| 63 | Lecture 63: Data with unequal weights | Download |
| 64 | Lecture 64: Robust estimates | Download |
| 65 | Lecture 65: From data to underlying distribution | Download |
| 66 | Lecture 66: Bootstrap method | Download |
| 67 | Lecture 67: Summary:Data processing | Download |
| 68 | Lecture 68: Hypothesis Testing I | Download |
| 69 | Lecture 69: Hypothesis Testing II | Download |
| 70 | Lecture 70: Hypothesis Testing III | Download |
| 71 | Lecture 71: Hypothesis Testing IV | Download |
| 72 | Lecture 72: Hypothesis Testing V | Download |
| 73 | Lecture 73: Hypothesis Testing VI | Download |
| 74 | Lecture 74: Graphical handling of data | Download |
| 75 | Lecture 75: Fitting and graphical handling of data: Introduction | Download |
| 76 | Lecture 76: Data transformable to linear | Download |
| 77 | Lecture 77: Data of known functional form | Download |
| 78 | Lecture 78: Calibration,Fitting,Hypotheses testing | Download |
| 79 | Lecture 79: Analysis of variance | Download |
| 80 | Lecture 80: Summary:Fittng and graphical handling of data | Download |
| 81 | Lecture 81: Regression Analysis - I | Download |
| 82 | Lecture 82: Regression Analysis - II | Download |
| 83 | Lecture 83: Regression Analysis - III | Download |
| 84 | Lecture 84: Regression Analysis - IV | Download |
| 85 | Lecture 85: Analysis of Variance-I | Download |
| 86 | Lecture 86: Analysis of Variance-II | Download |
| 87 | Lecture 87: Design of Experiment I | Download |
| 88 | Lecture 88: Design of Experiment II | Download |
| 89 | Lecture 89: Design of Experiment III | Download |
| 90 | Lecture 90: Design of Experiment IV | Download |
| 91 | Lecture 91: Summary of the course | Download |
| 92 | Lecture 92: Case studies: Introduction | Download |
| 93 | Lecture 93: Case study 1: Data smoothing I | Download |
| 94 | Lecture 94: Case study 1: Data smoothing II | Download |
| 95 | Lecture 95: Case study 2: Error analysis | Download |
| 96 | Lecture 96: Case study 3: Calibration | Download |
| 97 | Lecture 97: Case study 4: Design of experiment | Download |
| 98 | Lecture 98: Case study 5: Hypothesis testing | Download |
| 99 | Lecture 99: Course summary | Download |
| Sl.No | Chapter Name | English |
|---|---|---|
| 1 | Lecture 1: Descriptive Statistics-I | Download Verified |
| 2 | Lecture 2: Descriptive Statistics-II | Download Verified |
| 3 | Lecture 3: Probability and Distribution | Download Verified |
| 4 | Lecture 4: Random variable and Expectation I | Download Verified |
| 5 | Lecture 5: Random variable and Expectation II | Download Verified |
| 6 | Lecture 6: Random variable and Expectation III | Download Verified |
| 7 | Lecture 7: Random variable and Expectation IV | Download Verified |
| 8 | Lecture 8: Module: Introduction to R | Download Verified |
| 9 | Lecture 9: R : Demos and getting help | Download Verified |
| 10 | Lecture 10: R as calculator and plotter: Diffusivity, scaled temperatures | Download Verified |
| 11 | Lecture 11: R as calculator and plotter: Diffraction, configurational entropy | Download Verified |
| 12 | Lecture 12: Data in tabular form: Properties of elements | Download Verified |
| 13 | Lecture 13: Tabular data in R: alternate methodology | Download Verified |
| 14 | Lecture 14: Dataframe in R: Properties of elements | Download Verified |
| 15 | Lecture 15: R libraries for plotting | Download Verified |
| 16 | Lecture 16: Importing and plotting data | Download Verified |
| 17 | Lecture 17: Property charts: Importing and plotting data | Download Verified |
| 18 | Lecture 18: Introduction to R: Summary of the module | Download Verified |
| 19 | Lecture 19: Descriptive statistics | Download Verified |
| 20 | Lecture 20: Presenting experimental results: Data on conductivity of ETP copper | Download Verified |
| 21 | Lecture 21: Property based reports, errors, significant digits | Download Verified |
| 22 | Lecture 22: Dealing with distributions: Grain size data | Download Verified |
| 23 | Lecture 23: Grain size data: Property and rank based reports | Download Verified |
| 24 | Lecture 24: Case study: Grain size in a two phase steel | Download Verified |
| 25 | Lecture 25: Grain size in a two phase steel: Descriptive statistics | Download Verified |
| 26 | Lecture 26: Presenting experimental results: data with error bars | Download Verified |
| 27 | Lecture 27: Errors and their propagation | Download Verified |
| 28 | Lecture 28: Fitting experimental data to distributions | Download Verified |
| 29 | Lecture 29: Combining uncertainties | Download Verified |
| 30 | Lecture 30: Summary:Descriptive statistics | Download Verified |
| 31 | Lecture 31: Special Random Variables I | Download Verified |
| 32 | Lecture 32: Special Random Variables II | Download Verified |
| 33 | Lecture 33: Special Random Variables III | Download Verified |
| 34 | Lecture 34: Special Random Variables IV | Download Verified |
| 35 | Lecture 35: Special Random Variables V | Download Verified |
| 36 | Lecture 36: Probabilty Plots | Download Verified |
| 37 | Lecture 37: Probability distributions | Download Verified |
| 38 | Lecture 38: Properties of probability distributions | Download Verified |
| 39 | Lecture 39: Bernoulli trials and binomial distributions | Download Verified |
| 40 | Lecture 40: Atom probe technique and negative binomial distribution | Download Verified |
| 41 | Lecture 41: Atom probe and hypergeometric distribution | Download Verified |
| 42 | Lecture 42: Atom probe : analysis of error | Download Verified |
| 43 | Lecture 43: Nucleation and Poisson distribution | Download Verified |
| 44 | Lecture 44: Normal distribution | Download Verified |
| 45 | Lecture 45: Normal distribution and error function | Download Verified |
| 46 | Lecture 46: Probability scale | Download Verified |
| 47 | Lecture 47: Sampling Distribution I | Download Verified |
| 48 | Lecture 48: Sampling Distribution II | Download Verified |
| 49 | Lecture 49: Sampling Distribution III | Download Verified |
| 50 | Lecture 50: Parameter Estimation I | Download Verified |
| 51 | Lecture 51: Parameter Estimator II | Download Verified |
| 52 | Lecture 52: Parameter Estimator III | Download Verified |
| 53 | Lecture 53: Parameter Estimator IV | Download Verified |
| 54 | Lecture 54: Bayesian Estimation | Download Verified |
| 55 | Lecture 55: Log normal distribution | Download Verified |
| 56 | Lecture 56: Lorentz/Cauchy distribution | Download Verified |
| 57 | Lecture 57: Lifetime and exponential distributions | Download Verified |
| 58 | Lecture 58: Distributions from statistical mechanics | Download Verified |
| 59 | Lecture 59: Uniform distribution and summary of probability distributions | Download Verified |
| 60 | Lecture 60: Data processing: Introduction | Download Verified |
| 61 | Lecture 61: Distribution function of a data series | Download Verified |
| 62 | Lecture 62: Estimating mean and mean-square-deviation of data | Download Verified |
| 63 | Lecture 63: Data with unequal weights | Download Verified |
| 64 | Lecture 64: Robust estimates | Download Verified |
| 65 | Lecture 65: From data to underlying distribution | Download Verified |
| 66 | Lecture 66: Bootstrap method | Download Verified |
| 67 | Lecture 67: Summary:Data processing | Download Verified |
| 68 | Lecture 68: Hypothesis Testing I | Download Verified |
| 69 | Lecture 69: Hypothesis Testing II | Download Verified |
| 70 | Lecture 70: Hypothesis Testing III | Download Verified |
| 71 | Lecture 71: Hypothesis Testing IV | Download Verified |
| 72 | Lecture 72: Hypothesis Testing V | Download Verified |
| 73 | Lecture 73: Hypothesis Testing VI | Download Verified |
| 74 | Lecture 74: Graphical handling of data | Download Verified |
| 75 | Lecture 75: Fitting and graphical handling of data: Introduction | Download Verified |
| 76 | Lecture 76: Data transformable to linear | Download Verified |
| 77 | Lecture 77: Data of known functional form | Download Verified |
| 78 | Lecture 78: Calibration,Fitting,Hypotheses testing | Download Verified |
| 79 | Lecture 79: Analysis of variance | Download Verified |
| 80 | Lecture 80: Summary:Fittng and graphical handling of data | Download Verified |
| 81 | Lecture 81: Regression Analysis - I | Download Verified |
| 82 | Lecture 82: Regression Analysis - II | Download Verified |
| 83 | Lecture 83: Regression Analysis - III | Download Verified |
| 84 | Lecture 84: Regression Analysis - IV | Download Verified |
| 85 | Lecture 85: Analysis of Variance-I | Download Verified |
| 86 | Lecture 86: Analysis of Variance-II | Download Verified |
| 87 | Lecture 87: Design of Experiment I | Download Verified |
| 88 | Lecture 88: Design of Experiment II | Download Verified |
| 89 | Lecture 89: Design of Experiment III | Download Verified |
| 90 | Lecture 90: Design of Experiment IV | Download Verified |
| 91 | Lecture 91: Summary of the course | Download Verified |
| 92 | Lecture 92: Case studies: Introduction | Download Verified |
| 93 | Lecture 93: Case study 1: Data smoothing I | Download Verified |
| 94 | Lecture 94: Case study 1: Data smoothing II | Download Verified |
| 95 | Lecture 95: Case study 2: Error analysis | Download Verified |
| 96 | Lecture 96: Case study 3: Calibration | Download Verified |
| 97 | Lecture 97: Case study 4: Design of experiment | Download Verified |
| 98 | Lecture 98: Case study 5: Hypothesis testing | Download Verified |
| 99 | Lecture 99: Course summary | Download Verified |
| Sl.No | Language | Book link |
|---|---|---|
| 1 | English | Download |
| 2 | Bengali | Not Available |
| 3 | Gujarati | Not Available |
| 4 | Hindi | Not Available |
| 5 | Kannada | Not Available |
| 6 | Malayalam | Not Available |
| 7 | Marathi | Not Available |
| 8 | Tamil | Not Available |
| 9 | Telugu | Not Available |