Modules / Lectures
Module NameDownload


Sl.No Chapter Name MP4 Download
1Lecture 1: Descriptive Statistics-IDownload
2Lecture 2: Descriptive Statistics-IIDownload
3Lecture 3: Probability and DistributionDownload
4Lecture 4: Random variable and Expectation IDownload
5Lecture 5: Random variable and Expectation IIDownload
6Lecture 6: Random variable and Expectation IIIDownload
7Lecture 7: Random variable and Expectation IVDownload
8Lecture 8: Module: Introduction to RDownload
9Lecture 9: R : Demos and getting helpDownload
10Lecture 10: R as calculator and plotter: Diffusivity, scaled temperaturesDownload
11Lecture 11: R as calculator and plotter: Diffraction, configurational entropy Download
12Lecture 12: Data in tabular form: Properties of elementsDownload
13Lecture 13: Tabular data in R: alternate methodologyDownload
14Lecture 14: Dataframe in R: Properties of elementsDownload
15Lecture 15: R libraries for plottingDownload
16Lecture 16: Importing and plotting dataDownload
17Lecture 17: Property charts: Importing and plotting dataDownload
18Lecture 18: Introduction to R: Summary of the moduleDownload
19Lecture 19: Descriptive statisticsDownload
20Lecture 20: Presenting experimental results: Data on conductivity of ETP copperDownload
21Lecture 21: Property based reports, errors, significant digitsDownload
22Lecture 22: Dealing with distributions: Grain size dataDownload
23Lecture 23: Grain size data: Property and rank based reportsDownload
24Lecture 24: Case study: Grain size in a two phase steelDownload
25Lecture 25: Grain size in a two phase steel: Descriptive statisticsDownload
26Lecture 26: Presenting experimental results: data with error barsDownload
27Lecture 27: Errors and their propagationDownload
28Lecture 28: Fitting experimental data to distributionsDownload
29Lecture 29: Combining uncertaintiesDownload
30Lecture 30: Summary:Descriptive statisticsDownload
31Lecture 31: Special Random Variables IDownload
32Lecture 32: Special Random Variables IIDownload
33Lecture 33: Special Random Variables IIIDownload
34Lecture 34: Special Random Variables IVDownload
35Lecture 35: Special Random Variables VDownload
36Lecture 36: Probabilty PlotsDownload
37Lecture 37: Probability distributionsDownload
38Lecture 38: Properties of probability distributionsDownload
39Lecture 39: Bernoulli trials and binomial distributionsDownload
40Lecture 40: Atom probe technique and negative binomial distribution Download
41Lecture 41: Atom probe and hypergeometric distributionDownload
42Lecture 42: Atom probe : analysis of errorDownload
43Lecture 43: Nucleation and Poisson distributionDownload
44Lecture 44: Normal distributionDownload
45Lecture 45: Normal distribution and error functionDownload
46Lecture 46: Probability scaleDownload
47Lecture 47: Sampling Distribution IDownload
48Lecture 48: Sampling Distribution IIDownload
49Lecture 49: Sampling Distribution IIIDownload
50Lecture 50: Parameter Estimation IDownload
51Lecture 51: Parameter Estimator IIDownload
52Lecture 52: Parameter Estimator IIIDownload
53Lecture 53: Parameter Estimator IVDownload
54Lecture 54: Bayesian EstimationDownload
55Lecture 55: Log normal distributionDownload
56Lecture 56: Lorentz/Cauchy distributionDownload
57Lecture 57: Lifetime and exponential distributionsDownload
58Lecture 58: Distributions from statistical mechanicsDownload
59Lecture 59: Uniform distribution and summary of probability distributionsDownload
60Lecture 60: Data processing: IntroductionDownload
61Lecture 61: Distribution function of a data seriesDownload
62Lecture 62: Estimating mean and mean-square-deviation of dataDownload
63Lecture 63: Data with unequal weightsDownload
64Lecture 64: Robust estimatesDownload
65Lecture 65: From data to underlying distributionDownload
66Lecture 66: Bootstrap methodDownload
67Lecture 67: Summary:Data processingDownload
68Lecture 68: Hypothesis Testing IDownload
69Lecture 69: Hypothesis Testing IIDownload
70Lecture 70: Hypothesis Testing IIIDownload
71Lecture 71: Hypothesis Testing IVDownload
72Lecture 72: Hypothesis Testing VDownload
73Lecture 73: Hypothesis Testing VIDownload
74Lecture 74: Graphical handling of dataDownload
75Lecture 75: Fitting and graphical handling of data: IntroductionDownload
76Lecture 76: Data transformable to linear Download
77Lecture 77: Data of known functional formDownload
78Lecture 78: Calibration,Fitting,Hypotheses testingDownload
79Lecture 79: Analysis of varianceDownload
80Lecture 80: Summary:Fittng and graphical handling of dataDownload

Sl.No Chapter Name English
1Lecture 1: Descriptive Statistics-IDownload
Verified
2Lecture 2: Descriptive Statistics-IIDownload
Verified
3Lecture 3: Probability and DistributionDownload
Verified
4Lecture 4: Random variable and Expectation IDownload
Verified
5Lecture 5: Random variable and Expectation IIDownload
Verified
6Lecture 6: Random variable and Expectation IIIDownload
Verified
7Lecture 7: Random variable and Expectation IVDownload
Verified
8Lecture 8: Module: Introduction to RDownload
Verified
9Lecture 9: R : Demos and getting helpDownload
Verified
10Lecture 10: R as calculator and plotter: Diffusivity, scaled temperaturesDownload
Verified
11Lecture 11: R as calculator and plotter: Diffraction, configurational entropy Download
Verified
12Lecture 12: Data in tabular form: Properties of elementsDownload
Verified
13Lecture 13: Tabular data in R: alternate methodologyDownload
Verified
14Lecture 14: Dataframe in R: Properties of elementsDownload
Verified
15Lecture 15: R libraries for plottingDownload
Verified
16Lecture 16: Importing and plotting dataDownload
Verified
17Lecture 17: Property charts: Importing and plotting dataDownload
Verified
18Lecture 18: Introduction to R: Summary of the moduleDownload
Verified
19Lecture 19: Descriptive statisticsPDF unavailable
20Lecture 20: Presenting experimental results: Data on conductivity of ETP copperPDF unavailable
21Lecture 21: Property based reports, errors, significant digitsPDF unavailable
22Lecture 22: Dealing with distributions: Grain size dataPDF unavailable
23Lecture 23: Grain size data: Property and rank based reportsPDF unavailable
24Lecture 24: Case study: Grain size in a two phase steelPDF unavailable
25Lecture 25: Grain size in a two phase steel: Descriptive statisticsPDF unavailable
26Lecture 26: Presenting experimental results: data with error barsPDF unavailable
27Lecture 27: Errors and their propagationPDF unavailable
28Lecture 28: Fitting experimental data to distributionsPDF unavailable
29Lecture 29: Combining uncertaintiesPDF unavailable
30Lecture 30: Summary:Descriptive statisticsPDF unavailable
31Lecture 31: Special Random Variables IPDF unavailable
32Lecture 32: Special Random Variables IIPDF unavailable
33Lecture 33: Special Random Variables IIIPDF unavailable
34Lecture 34: Special Random Variables IVPDF unavailable
35Lecture 35: Special Random Variables VPDF unavailable
36Lecture 36: Probabilty PlotsPDF unavailable
37Lecture 37: Probability distributionsPDF unavailable
38Lecture 38: Properties of probability distributionsPDF unavailable
39Lecture 39: Bernoulli trials and binomial distributionsPDF unavailable
40Lecture 40: Atom probe technique and negative binomial distribution PDF unavailable
41Lecture 41: Atom probe and hypergeometric distributionPDF unavailable
42Lecture 42: Atom probe : analysis of errorPDF unavailable
43Lecture 43: Nucleation and Poisson distributionPDF unavailable
44Lecture 44: Normal distributionPDF unavailable
45Lecture 45: Normal distribution and error functionPDF unavailable
46Lecture 46: Probability scalePDF unavailable
47Lecture 47: Sampling Distribution IPDF unavailable
48Lecture 48: Sampling Distribution IIPDF unavailable
49Lecture 49: Sampling Distribution IIIPDF unavailable
50Lecture 50: Parameter Estimation IPDF unavailable
51Lecture 51: Parameter Estimator IIPDF unavailable
52Lecture 52: Parameter Estimator IIIPDF unavailable
53Lecture 53: Parameter Estimator IVPDF unavailable
54Lecture 54: Bayesian EstimationPDF unavailable
55Lecture 55: Log normal distributionPDF unavailable
56Lecture 56: Lorentz/Cauchy distributionPDF unavailable
57Lecture 57: Lifetime and exponential distributionsPDF unavailable
58Lecture 58: Distributions from statistical mechanicsPDF unavailable
59Lecture 59: Uniform distribution and summary of probability distributionsPDF unavailable
60Lecture 60: Data processing: IntroductionPDF unavailable
61Lecture 61: Distribution function of a data seriesPDF unavailable
62Lecture 62: Estimating mean and mean-square-deviation of dataPDF unavailable
63Lecture 63: Data with unequal weightsPDF unavailable
64Lecture 64: Robust estimatesPDF unavailable
65Lecture 65: From data to underlying distributionPDF unavailable
66Lecture 66: Bootstrap methodPDF unavailable
67Lecture 67: Summary:Data processingPDF unavailable
68Lecture 68: Hypothesis Testing IPDF unavailable
69Lecture 69: Hypothesis Testing IIPDF unavailable
70Lecture 70: Hypothesis Testing IIIPDF unavailable
71Lecture 71: Hypothesis Testing IVPDF unavailable
72Lecture 72: Hypothesis Testing VPDF unavailable
73Lecture 73: Hypothesis Testing VIPDF unavailable
74Lecture 74: Graphical handling of dataPDF unavailable
75Lecture 75: Fitting and graphical handling of data: IntroductionPDF unavailable
76Lecture 76: Data transformable to linear PDF unavailable
77Lecture 77: Data of known functional formPDF unavailable
78Lecture 78: Calibration,Fitting,Hypotheses testingPDF unavailable
79Lecture 79: Analysis of variancePDF unavailable
80Lecture 80: Summary:Fittng and graphical handling of dataPDF unavailable


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7MarathiNot Available
8TamilNot Available
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