10 - Selecting & Summarizing Column(s) Stats in one step with Julia and R #shorts
#shorts To select a specific column, tidyverse uses, fair enough, the select() function. Notice that the resulting output is ordered alphabetically. To calculate some basic statistics of a selected numeric column, you can use summary(). Julia offers its own select() function and you need to combine it with the sort!() function to get the same output with R's select(), while for basic summary statistics, describe() displays a richer set of information, since apart from the quartile and the mean it also include the number of missing values and the numeric type of the column.
0:15 The motivation to learn Julia
1:40 The purpose of the video
2:00 The setting for running Julia
3:35 Loading the GLM, DataFrames and CSV packages
7:19 About the GLC sample data in GLC_test4.csv
7:54 Importing the data as a DataFrame
9:32 Preparing functions for replacing commas by dots and converting strings into floating point numbers
11:48 Fitting a model to the data with lm()
12:26 Comparing Julia's lm() with R's summary(lm))
13:53 Finding the r-squared index with Julia
14:26 Conducting the partial F-test with Julia
15:35 Getting the fields of an object
The Julia source file used in the video:
https://github.com/atantos/Youtube/blob/master/Simple_LR.jl
The github link of the GLC_test4.csv file:
https://raw.githubusercontent.com/atantos/Youtube/master/GLC_test4.csv
Julia's official site:
https://julialang.org/
The Intro and Outro song by Admonisher:
https://www.youtube.com/watch?v=D0HWQbzEVhM
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https://www.youtube.com/watch?v=_zS-MFy5CqA
A short introductory video for the participants of the spring school on experimental and corpus linguistics in Thessaloniki
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https://www.youtube.com/watch?v=VW5jm0GLwQg
One of the strengths of tidyverse is to very easily create new or change existing dataframe columns by using mutate().
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https://www.youtube.com/watch?v=67uGoVTrjQc
Ηχητικό αρχείο της συνέντευξης που δόθηκε στην κ. Δόικου για την εκπομπή "Εκ βαθέων" του δημοτικού ραδιοφώνου Θεσσαλονίκης, fm100. Η συνέντευξη αφορά τον κύκλο διαλέξεων "Ο αντίκτυπος της ΤΝ σήμερα και αύριο" που διοργανώνεται από το εργαστήριο LingLab του τομέα γλωσσσολογίας του Τμήματος Φιλολογίας του Αριστοτελείου Πανεπιστημίου Θεσσαλονίκης.
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https://www.youtube.com/watch?v=U-ycaH5lRVA
In this tutorial, it's about time to dig a bit deeper into character vectors and answer the question:
- How do you retrieve values out of character vectors?
For answering this question, this video will focus on the first of the three different ways of subsetting a vector in R, namely by using the indexing of a character vector. The others will be presented in the next tutorials.
- 0:10 Defining indexing
- 2:02 3 ways of subsetting a character vector
- 2:19 How do you subset a character vector with indices?
- 3:15 The range operator ":"
- 4:08 Subsetting with a vector of indices
- 5:05 The exclusion or minus operator "-"
- 7:01 Code summary
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https://www.youtube.com/watch?v=R9vqJTJFvoQ
Welcome back to Categorical Data Analysis with Julia!
Today, we're going to break down the output of the logistic regression model we created in the previous short video.
Our model is predicting the probability of 'Survived' based on the 'Pclass' variable. Recall that 'Pclass 1' stands for first class, Pclass 2 for second class, and Pclass 3 for third class.
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https://www.youtube.com/watch?v=46G6YAWV6Es
Our school includes a three-day compact course on experimental and corpus linguistics. The participants will acquire the necessary knowledge to handle corpora and experimental data sets for research and teaching purposes. The sessions will involve lectures and lab practice. Sessions will include a) practice to design off-line and on-line linguistic experiments, b) programming practice for corpus construction and data manipulation and analysis (using XML and R) and c) practical introduction to statistical modelling of linguistic data (e.g. mixed effects models using R). For both experimental and corpus linguistic sessions, data sets from real studies will be used and analysed.
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https://www.youtube.com/watch?v=NfjXyYzLQag
#shorts #shortvideo
Welcome back to Categorical Data Analysis with Julia! In this video, we will fit a logistic regression model.
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https://www.youtube.com/watch?v=n18_TuSaATE
CHAPTERS:
0:00 Intro
0:10 From Strings to Categorical Variables
1:06 Frequency Distributions & Cross-Tabulations
2:01 Data Visualization: Grouped Barplots
2:53 Inferential Stats with Julia: Chi-squared Test of Independence
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https://www.youtube.com/watch?v=Y3ygWwZEw08