Modules / Lectures
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Sl.No Chapter Name MP4 Download Transcript Download
1Lecture 1: Descriptive Statistics-IDownloadDownload
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2Lecture 2: Descriptive Statistics-IIDownloadDownload
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3Lecture 3: Probability and DistributionDownloadDownload
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4Lecture 4: Random variable and Expectation IDownloadDownload
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5Lecture 5: Random variable and Expectation IIDownloadDownload
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6Lecture 6: Random variable and Expectation IIIDownloadDownload
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7Lecture 7: Random variable and Expectation IVDownloadDownload
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8Lecture 8: Module: Introduction to RDownloadDownload
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9Lecture 9: R : Demos and getting helpDownloadDownload
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10Lecture 10: R as calculator and plotter: Diffusivity, scaled temperaturesDownloadDownload
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11Lecture 11: R as calculator and plotter: Diffraction, configurational entropy DownloadDownload
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12Lecture 12: Data in tabular form: Properties of elementsDownloadDownload
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13Lecture 13: Tabular data in R: alternate methodologyDownloadDownload
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14Lecture 14: Dataframe in R: Properties of elementsDownloadDownload
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15Lecture 15: R libraries for plottingDownloadDownload
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16Lecture 16: Importing and plotting dataDownloadDownload
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17Lecture 17: Property charts: Importing and plotting dataDownloadDownload
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18Lecture 18: Introduction to R: Summary of the moduleDownloadDownload
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19Lecture 19: Descriptive statisticsDownloadPDF unavailable
20Lecture 20: Presenting experimental results: Data on conductivity of ETP copperDownloadPDF unavailable
21Lecture 21: Property based reports, errors, significant digitsDownloadPDF unavailable
22Lecture 22: Dealing with distributions: Grain size dataDownloadPDF unavailable
23Lecture 23: Grain size data: Property and rank based reportsDownloadPDF unavailable
24Lecture 24: Case study: Grain size in a two phase steelDownloadPDF unavailable
25Lecture 25: Grain size in a two phase steel: Descriptive statisticsDownloadPDF unavailable
26Lecture 26: Presenting experimental results: data with error barsDownloadPDF unavailable
27Lecture 27: Errors and their propagationDownloadPDF unavailable
28Lecture 28: Fitting experimental data to distributionsDownloadPDF unavailable
29Lecture 29: Combining uncertaintiesDownloadPDF unavailable
30Lecture 30: Summary:Descriptive statisticsDownloadPDF unavailable
31Lecture 31: Special Random Variables IDownloadPDF unavailable
32Lecture 32: Special Random Variables IIDownloadPDF unavailable
33Lecture 33: Special Random Variables IIIDownloadPDF unavailable
34Lecture 34: Special Random Variables IVDownloadPDF unavailable
35Lecture 35: Special Random Variables VDownloadPDF unavailable
36Lecture 36: Probabilty PlotsDownloadPDF unavailable