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| − | * Instructors: Ilya Schurov and Olga Lyashevskaya | + | == Школа лингвистики == |
| | + | * [[Теория вероятностей и математическая статистика]] (2 курс) |
| | + | * [[Linguistic Data: Quantitative Analysis and Visualisation: computational linguistics]] |
| | + | * [[Linguistic Data: Quantitative Analysis and Visualisation: linguistic theory]] |
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| − | == Materials == | + | == Совместный бакалавриат ВШЭ и РЭШ == |
| − | {| class="wikitable"
| + | * [[Дифференциальные уравнения]] |
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| + | * [[Наука о данных]] |
| − | ! Data !! Topics !! Links
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| − | | Jan 18 || Introduction. Quantitative linguistic research and data types. R basics || [https://docs.google.com/presentation/d/1VUIUa3Db5n4dsD_HeA3e-mz55zK8uPrko3yu207pKUk/edit?usp=sharing Intro Slides] [https://github.com/LingData2019/LingData2020/tree/master/seminars/2020-01-18 Lab 01: intro to R]
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| − | | Jan 25 || Hypothesis testing. Binomial test. R: dataframes || [https://rpubs.com/ilyaschurov/rdataframes2020theo lab02]
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| − | | Feb 1
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| − | | Estimating of population mean. Central Limit Theorem
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| − | | Feb 8
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| − | | One sample t-test. Working with dataframes. Selection by condition.
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| − | | Feb 15
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| − | | Two sample t-test. Usage of <code>t.test</code> to perform two-sample t.test.
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| − | | [https://rpubs.com/ilyaschurov/ttest2-2020 notebook]
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| − | |}
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| − | == Homeworks == | + | == ОП Политология == |
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| + | * [[Математические модели политэкономии]] |
| − | ! id !! links !! due date !! upload link
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| − | | HW1
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| − | | [https://github.com/LingData2019/LingData2020/blob/master/hw/LingData-HW1-theo.Rmd Rmd], [https://github.com/LingData2019/LingData2020/blob/master/hw/LingData-HW1-theo.pdf pdf]
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| − | | Feb. 9, 23:59:59
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| − | | [https://www.dropbox.com/request/hblqeftXqVpJLj0miQwd here]
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| − | | HW2
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| − | | [https://github.com/LingData2019/LingData2020/blob/master/hw/LingData-HW2-theo.Rmd Rmd], [https://github.com/LingData2019/LingData2020/blob/master/hw/hw-pdf/LingData-HW2-theo.pdf pdf]
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| − | | Feb. 24, 23:59:59
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| − | | [https://www.dropbox.com/request/TTMCHN0AOZ1MONaPjuav here]
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| − | |}
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| − | == Software == | + | == Факультет математики == |
| − | During this course we will use R as a programming language and RStudio as a GUI.
| + | * [http://wiki.cs.hse.ru/Машинное_обучение_на_матфаке_2020 Машинное обучение] |
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| − | How to install R and RStudio?
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| − | 1. Download [https://cran.r-project.org/ R] (you can choose another mirror here if you wish) and install it on your computer. Make sure you did it before installing RStudio.
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| − | 2. Download [https://rstudio.com/products/rstudio/ RStudio] (you need RStudio Desktop Open Source License) and install it on your computer. It is recommended to create a shortcut for RStudio during installation.
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| − | It is possible avoid installing anything on your PC, using [https://rstudio.cloud rstudio.cloud] (an online version of RStudio).
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| − | For successful submission of assignments you should be able to create and save R code files (.R) and RMarkdown files (.Rmd).
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