1977     black mirror s03     x expedition x s06e03     p4a     1977     baldur's gate 3     Iron Fist s01     rayveness     The.Seed.of.the.Sacred.Fig     1977     Naked     1977     a-bout-de-souffle-1960     1977     p4a     lost city     Murdaugh Murders: A Southern Scandal     Wicked.     1080p x264     fl studio producer edition    

Udemy - First steps in data analysis with R

seeders: 0
leechers: 0
Added 4 years ago by freecoursewb in Other

Download Fast Safe Anonymous
movies, software, shows...

Files

Udemy - First steps in data analysis with R (Size: 1.2 GB)
  01 - first steps.R 1.4 KB
  02a - compare two groups with ttest.R 2.3 KB
  02b - compare two groups with ttest on data from dataframe.R 3.8 KB
  02c - compare two groups with lm.R 5.5 KB
  03 - compare more than two groups.R 6.4 KB
  04 - linear regression.R 3.3 KB
  05 - Intro to ggplot.R 3.2 KB
  06 - testing the effects of factorial + continuous predictors.R 7 KB
  07 - testing the effect of two factorial predictors.R 5.7 KB
  08 - testing the effect of two continuous predictors.R 4.9 KB
  09 - polynomial regression.R 2.6 KB
  1. A panoramic of some data-wrangling tools.mp4 55.7 MB
  1. A panoramic of some data-wrangling tools.srt 8.4 KB
  1. An example using function nls().mp4 91.7 MB
  1. An example using function nls().srt 9.5 KB
  1. An example with count data.mp4 20.3 MB
  1. An example with count data.srt 8.2 KB
  1. Comparing more than two groups with lm().mp4 133.6 MB
  1. Comparing more than two groups with lm().srt 17.4 KB
  1. Concepts, scenarios, and worked example.mp4 97.1 MB
  1. Concepts, scenarios, and worked example.srt 15.2 KB
  1. Example 1.mp4 52.3 MB
  1. Example 1.srt 6.8 KB
  1. Final remarks.mp4 10.6 MB
  1. Final remarks.srt 5.2 KB
  1. Housework on a Mac.mp4 16.2 MB
  1. Housework on a Mac.srt 2.8 KB
  1. How to produce and interpret diagnostic plots.mp4 33.3 MB
  1. How to produce and interpret diagnostic plots.srt 9.3 KB
  1. Introducing lm() - example comparing two groups.mp4 68.6 MB
  1. Introducing lm() - example comparing two groups.srt 9.8 KB
  1. Introduction to ggplot2.mp4 99.3 MB
  1. Introduction to ggplot2.srt 11.1 KB
  1. Introduction.mp4 19.7 MB
  1. Introduction.srt 1.8 KB
  1. Performing linear regression in R.mp4 47.9 MB
  1. Performing linear regression in R.srt 6.8 KB
  1. Scenarios and worked example.mp4 128.6 MB
  1. Scenarios and worked example.srt 16.3 KB
  1. t.test() - part 1.mp4 20.1 MB
  1. t.test() - part 1.srt 9.1 KB
  1.1 02a - compare two groups with ttest.R 2.3 KB
  1.1 02c - compare two groups with lm.R 5.5 KB
  1.1 03 - compare more than two groups.R 6.4 KB
  1.1 04 - linear regression.R 3.3 KB
  1.1 05 - Intro to ggplot.R 3.2 KB
  1.1 06 - testing the effects of factorial + continuous predictors.R 7 KB
  1.1 07 - testing the effect of two factorial predictors.R 5.7 KB
  1.1 08 - testing the effect of two continuous predictors.R 4.9 KB
  1.1 09 - polynomial regression.R 2.6 KB
  1.1 10 - non-linear modelling.R 4.2 KB
  1.1 11 - glm Poisson.R 3.8 KB
  1.1 12 - data wrangling.R 3.9 KB
  1.1 Manuals and other resources.pdf 56.3 KB
  1.1 ancova.pdf 117.9 KB
  1.1 housework mac.R 204.8 B
  1.2 ANCOVA_data.csv 3.7 KB
  1.2 anova1.pdf 453.9 KB
  1.2 anova_type2_data.csv 13.7 KB
  1.2 compare_2_species.csv 2.9 KB
  1.2 compare_6_species.txt 46.5 KB
  1.2 count_data.csv 1.8 KB
  1.2 multi_reg_data.csv 7 KB
  1.2 non_linear_datasets.xlsx 54.1 KB
  1.2 regression_data.csv 716.8 B
  1.3 GLM resources.pdf 43.5 KB
  1.3 anova2.pdf 152.1 KB
  1.3 regression_data.csv 716.8 B
  1.4 multi_reg.pdf 138.8 KB
  1.5 non_linear.pdf 161.5 KB
  1.6 poisson.pdf 242.6 KB
  1.7 poly2.pdf 72.7 KB
  1.8 sim_heterosc.pdf 87.3 KB
  10 - non-linear modelling.R 4.2 KB
  11 - glm Poisson.R 3.8 KB
  12 - data wrangling.R 3.9 KB
  2. Evaluating diagnostic plots for a linear regression.mp4 5.8 MB
  2. Evaluating diagnostic plots for a linear regression.srt 4.3 KB
  2. Example 2.mp4 26.1 MB
  2. Example 2.srt 3.3 KB
  2. Housework on a Windows machine.mp4 20.9 MB
  2. Housework on a Windows machine.srt 2.4 KB
  2. Installing R.mp4 34.6 MB
  2. Installing R.srt 5.4 KB
  2. t.test() - part 2.mp4 72.2 MB
  2. t.test() - part 2.srt 8.8 KB
  2.1 02b - compare two groups with ttest on data from dataframe.R 3.8 KB
  2.1 housework windows.R 512 B
  2.2 compare_2_species.csv 2.9 KB
  3. Housework in RStudio.mp4 23.4 MB
  3. Housework in RStudio.srt 3.3 KB
  3. Writing code and creating object in the R console.mp4 4.7 MB
  3. Writing code and creating object in the R console.srt 1 KB
  4. Housework - final remarks.mp4 5.1 MB
  4. Housework - final remarks.srt 1.1 KB
  4. Your first R script.mp4 24.2 MB
  4. Your first R script.srt 5.3 KB
  4.1 01 - first steps.R 1.4 KB
  5. Your first graph.mp4 9.5 MB
  5. Your first graph.srt 2 KB
  6. Your second graph.mp4 40.5 MB
  6. Your second graph.srt 6.4 KB
  7. Saving figures on a Windows machine.mp4 15.4 MB
  7. Saving figures on a Windows machine.srt 2.1 KB
  ANCOVA_data.csv 3.7 KB
  Bonus Resources.txt 307.2 B
  DS_Store 6 KB
  Get Bonus Downloads Here.url 204.8 B
  Rapp.history 6.3 KB
  _.DS_Store 102.4 B
  _01 - first steps.R 204.8 B
  _02a - compare two groups with ttest.R 307.2 B
  _02b - compare two groups with ttest on data from dataframe.R 307.2 B
  _02c - compare two groups with lm.R 307.2 B
  _03 - compare more than two groups.R 204.8 B
  _04 - linear regression.R 204.8 B
  _05 - Intro to ggplot.R 307.2 B
  _06 - testing the effects of factorial + continuous predictors.R 204.8 B
  _07 - testing the effect of two factorial predictors.R 204.8 B
  _08 - testing the effect of two continuous predictors.R 307.2 B
  _09 - polynomial regression.R 307.2 B
  _10 - non-linear modelling.R 307.2 B
  _11 - glm Poisson.R 307.2 B
  _12 - data wrangling.R 204.8 B
  anova_type2_data.csv 13.7 KB
  compare_2_species.csv 2.9 KB
  compare_6_species.txt 46.5 KB
  count_data.csv 1.8 KB
  diel_activity_data.csv 7.3 KB
  multi_reg_data.csv 7 KB
  non_linear_datasets.xlsx 54.1 KB
  pairwise_tests.csv 1.5 KB
  poly_data1.csv 1.4 KB
  poly_data2.csv 2.3 KB
  regression_data.csv 716.8 B
  ▲ 141 total files

Description


First steps in data analysis with R
https://FreeCourseWeb.com

MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 28 lectures (2h 50m) | Size: 1.17 GB
Data analysis from zero to hero
What you'll learn:
Develop a reliable data analysis framework
Refresh your statistical knowledge in a visual, intuitive way
Visualise your data with publication-ready figures
Become confident with testing general linear models: regression, ANOVA, etc.
Learn and apply the principles of hypothesis testing and model selection
Introduction to generalised linear models and to non-linear modelling

Requirements
No programming experience needed. You'll learn how to use R from absolute 0.
You should be familiar with statistical concepts covered in any introductory statistics course, such as: Normal distribution, model parameters, variance, standard deviation, standard error, F-test, p-value.

Description
This course is aimed at those that already have a theoretical understanding of statistical concepts and want to learn the practical side of data analysis.

Learning how to analyse data can be a daunting test. Applying the statistical knowledge learned from books to real-world scenarios can be challenging, and it's often made harder by seemingly complicated data analysis softwares.

Related Torrents

torrent name size uploader age seed leech
0
0
5
11
13