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[ FreeCourseWeb com ] Udemy - First steps in data analysis with R
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1. Introduction
1. Introduction.mp4
1. Introduction.srt
1.1 ancova.pdf
1.2 anova1.pdf
1.3 anova2.pdf
1.4 multi_reg.pdf
1.5 non_linear.pdf
1.6 poisson.pdf
1.7 poly2.pdf
1.8 sim_heterosc.pdf
2. Installing R.mp4
2. Installing R.srt
3. Writing code and creating object in the R console.mp4
3. Writing code and creating object in the R console.srt
4. Your first R script.mp4
4. Your first R script.srt
4.1 01 - first steps.R
5. Your first graph.mp4
5. Your first graph.srt
6. Your second graph.mp4
6. Your second graph.srt
7. Saving figures on a Windows machine.mp4
7. Saving figures on a Windows machine.srt
First steps in data analysis with R byMarco Plebani - all scripts and data
DS_Store
my_data
ANCOVA_data.csv
DS_Store
Rapp.history
anova_type2_data.csv
compare_2_species.csv
compare_6_species.txt
count_data.csv
diel_activity_data.csv
multi_reg_data.csv
non_linear_datasets.xlsx
pairwise_tests.csv
poly_data1.csv
poly_data2.csv
regression_data.csv
my_scripts ANNOTATED
01 - first steps.R
02a - compare two groups with ttest.R
02b - compare two groups with ttest on data from dataframe.R
02c - compare two groups with lm.R
03 - compare more than two groups.R
04 - linear regression.R
05 - Intro to ggplot.R
06 - testing the effects of factorial + continuous predictors.R
07 - testing the effect of two factorial predictors.R
08 - testing the effect of two continuous predictors.R
09 - polynomial regression.R
10 - non-linear modelling.R
11 - glm Poisson.R
12 - data wrangling.R
__MACOSX
First steps in data analysis with R byMarco Plebani - all scripts and data
_.DS_Store
my_data
_.DS_Store
my_scripts ANNOTATED
_01 - first steps.R
_02a - compare two groups with ttest.R
_02b - compare two groups with ttest on data from dataframe.R
_02c - compare two groups with lm.R
_03 - compare more than two groups.R
_04 - linear regression.R
_05 - Intro to ggplot.R
_06 - testing the effects of factorial + continuous predictors.R
_07 - testing the effect of two factorial predictors.R
_08 - testing the effect of two continuous predictors.R
_09 - polynomial regression.R
_10 - non-linear modelling.R
_11 - glm Poisson.R
_12 - data wrangling.R
10. Testing the effect of two factorial predictors on a response variable
1. Concepts, scenarios, and worked example.mp4
1. Concepts, scenarios, and worked example.srt
1.1 07 - testing the effect of two factorial predictors.R
1.2 anova_type2_data.csv
11. Multiple regression
1. Scenarios and worked example.mp4
1. Scenarios and worked example.srt
1.1 08 - testing the effect of two continuous predictors.R
1.2 multi_reg_data.csv
12. Polynomial regression
1. Example 1.mp4
1. Example 1.srt
1.1 09 - polynomial regression.R
1.2 non_linear_datasets.xlsx
2. Example 2.mp4
2. Example 2.srt
13. Fitting user-defined non-linear models
1. An example using function nls().mp4
1. An example using function nls().srt
1.1 10 - non-linear modelling.R
1.2 non_linear_datasets.xlsx
14. Dealing with non-normality of residuals
1. An example with count data.mp4
1. An example with count data.srt
1.1 11 - glm Poisson.R
1.2 count_data.csv
1.3 GLM resources.pdf
15. Data wrangling
1. A panoramic of some data-wrangling tools.mp4
1. A panoramic of some data-wrangling tools.srt
1.1 12 - data wrangling.R
16. Final remarks
1. Final remarks.mp4
1. Final remarks.srt
1.1 Manuals and other resources.pdf
2. Housework
1. Housework on a Mac.mp4
1. Housework on a Mac.srt
1.1 housework mac.R
2. Housework on a Windows machine.mp4
2. Housework on a Windows machine.srt
2.1 housework windows.R
3. Housework in RStudio.mp4
3. Housework in RStudio.srt
4. Housework - final remarks.mp4
4. Housework - final remarks.srt
3. Comparing two groups with t.test()
1. t.test() - part 1.mp4
1. t.test() - part 1.srt
1.1 02a - compare two groups with ttest.R
2. t.test() - part 2.mp4
2. t.test() - part 2.srt
2.1 02b - compare two groups with ttest on data from dataframe.R
2.2 compare_2_species.csv
4. Introducing function lm()
1. Introducing lm() - example comparing two groups.mp4
1. Introducing lm() - example comparing two groups.srt
1.1 02c - compare two groups with lm.R
1.2 compare_2_species.csv
5. Testing model assumptions with diagnostic plots
1. How to produce and interpret diagnostic plots.mp4
1. How to produce and interpret diagnostic plots.srt
6. Comparing more than two groups an ANOVA scenario
1. Comparing more than two groups with lm().mp4
1. Comparing more than two groups with lm().srt
1.1 03 - compare more than two groups.R
1.2 compare_6_species.txt
7. Linear regression
1. Performing linear regression in R.mp4
1. Performing linear regression in R.srt
1.1 04 - linear regression.R
1.2 regression_data.csv
2. Evaluating diagnostic plots for a linear regression.mp4
2. Evaluating diagnostic plots for a linear regression.srt
8. Advanced data visualization with ggplot2
1. Introduction to ggplot2.mp4
1. Introduction to ggplot2.srt
1.1 05 - Intro to ggplot.R
1.2 compare_6_species.txt
1.3 regression_data.csv
9. An ANCOVA scenario testing the effect of two predictors on a response variable
1. Concepts, scenarios, and worked example.mp4
1. Concepts, scenarios, and worked example.srt
1.1 06 - testing the effects of factorial + continuous predictors.R
1.2 ANCOVA_data.csv
Bonus Resources.txt
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