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Rob K Statistics
Приєднався 16 жов 2018
QMUL Savannah Ecology Camera Trap Highlights September 2022
Not a stats video! These are highlights from a camera trap survey of mammal biodiversity carried out by students on our Savannah Ecology and Conservation field course in September 2022.
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Відео
R Markdown Course Part 2
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Part 2 of the R Markdown course. Again probably only of interest if you were there.
R Markdown course part 1
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Recording of an online R Markdown course. Probably only of interest if you were there. Useful links: research.sbcs.qmul.ac.uk/r.knell/Rmarkdown_formatting.html research.sbcs.qmul.ac.uk/r.knell/Example_document.html
Linear models in R: Principles of Model Selection
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When we're fitting statistical models, how do we decide on a set of candidate models, and how to we choose between those candidate models?
ANOVA coefficients tables in R explained
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The coefficients tables that R produces for linear models are a frequent source of confusion. Here we run through how we can interpret these for single and multiple factor ANOVA-type models.
Correlation analysis
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Correlation explained: how to calculate a correlation coefficient, what it means, how to test for significance and how to do it in R
T-tests Part 2: Two-sample t-test
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The basics behind the two sample t-test explained, along with interpretation and how to do one in R.
T-tests Part 1: Paired-sample t-test
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How does a paired sample t-test work, what does it mean and how to do it in R
Linear Regression 2: partitioning variance and statistical significance
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How partitioning variance works in a linear regression and how we can construct an ANOVA table to carry out a statistical significance test
Linear Regression 1: finding the line of best fit
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How to calculate the intercept and slope of a best fit line in linear regression
Generating an ANOVA table from partitioned variance
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This video follows on from "Partitioning Variance for ANOVA" and explains how to generate an ANOVA table from the sums of squares calculated when you partition your variance
Assumptions and Diagnostics for ANOVA, Regression and more complex Linear Models
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ANOVA, Linear Regression and the more complex analyses that make up the General Linear Model all rely on certain assumptions about the data being analysed. In this video I explain what these assumptions are and how they can be checked using the diagnostic plots that can be produced when a linear model is fitted.
Partitioning Variance For ANOVA and linear modelling
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Partitioning variance is the fundamental process underlying analyses such as ANOVA, linear regression and the general linear model. Here I explain how it works in a straightforward way using an ANOVA-type example.
RStudio code editing tips and shortcuts
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RStudio code editing tips: Keyboard shortcuts, Bracket matching, Reformat and reindent code, Duplicate lines, Autocomplete, Find and replace, Code sections, Code folding, Document outline, Snippets
Ordination using NMDS (Non-metric multidimensional scaling)
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Ordination using NMDS (Non-metric multidimensional scaling)
Regression and Linear Model Coefficients in R
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Regression and Linear Model Coefficients in R
This explaination was very helpful. It was very clear.
Amazing Vid!!!!!!!
An excellent video, thanks Rob!
great illustrations
Thank you so much for your videos, Rob! Very much appreciated!!
Thank you so much it is really informative course
What went inside ordihull () ? and points() ? I tried with ordi1 and I got error messages 😅
Thank you for this. I loved the below use ctrl+P to move between beginning and end of brackets shift+ctrl+ D to duplicate a line select the word you want to replace and then Ctrl+e to open the replace window alt+ctrl+shift+m to rename in scope
Brilliant! Thank you so much for the clear explanation!!!
Best explanation ever
Such a great video! Thank you!!!
Very nice vidieo sir..... Can you make vidieo on another project with code
Never understood what was going on with NMDS until now. Great video
Bless you! This helps so much!!
Thank you for your videos.
Thank you for this tutorial, it's incredibly helpful! I was struggling with understanding the model summary in class but now I get it
.... Can we do the same analysis for a single species instead of community ..? Could you please help me with this ...
If you want to estimate population sizes there are related techniques based on mark-recapture techniques (Have a look at Bill Sutherland's book on Ecological Census Techniques) but that's the only thing I can think of that's similar but for a single species only.
Thanks a lot for uploading all of this really helpful material!
Thanks Rob, really helpful!
Thank You so Much. Its very helpful material.
thanks mate for this; is there a way to split tables to fit available space in slides
This was very well explained, thank you !!
Good explanation teacher. The visuals help explain the concept better.
Mate, I never understood this and you've helped heaps! Thank you! :)
Las Vegas, NV, USA: Excellent assistance! Clear, well-paced. Really appreciated the tips on our ability to modify CVS on-the-fly in the View tab, and demonstrating the different ways to search. I had no idea you could search for something inside a file. Thanks, Rob!
Thank you! Glad you found it useful.
Hey I'm in Las Vegas also! Thank you Rob for the tutorial 😊
DAMN, YOU EXPLAINED IT SO NICELY. I get it now! thank you so much! subscribed!
Thank you! Great explanation!
Can you please upload the source code for this projcet
Thank you, this video was great!
What’s the keyboard shortcut to show the keyboard shortcut reference
Go to help -> keyboard shortcuts help. On a Mac the shortcut for this is option-shift-K.
amazing explanation! thanks!
Ty!
Thank you very much! Very helpful.
Thank you for such a good explanation, very precise. I have a problem, I'm unable to draw a good line for factor levels after color-coding them, I have used your codes but not working for me, do I need to add a library?
Hi Rob, Thanks for this excellent video. I have a question about the small difference between the intercept values in the without-interaction model (149.2698) and the with-interaction model (148.9856). I can see why these values are different: in the without-interaction model, the slopes have to be parallel, but in the with-interaction model this requirement is relaxed. I also get that, in the with-interaction model, the intercept value is the mean of the two reference levels, since this is the ‘full’ model (i.e., with no loss of info). My question is: how do we calculate the intercept value in the without-interaction model? In other words, what exactly is the source of the small difference between 149.2698 and 148.9856?
great explaination
What a well done video - thank you!
Perfect!
You are actually now my hero.
Thank you for this.. just started learning statistics for R. You are a blessing sir.
These vids are seriously great! Thanks, man!
Very useful! Thanks!
Well explained 👌
Another excellent video. Thanks Rob.
Thanks for the explanation! Could you please give a link or explain the code you used to construct the specaccum graph in R?
does this work on windoes operation system?
Certainly does: some of the menus and keyboard shortcuts might be different but that's all.
@@robkstatistics8224 okay thank you!
A simple, clear, to-the-point explanation. Thank you.
Excellent! Thank you so much for the easy explanation!
I got a stress value of 0.21. So, what means my value? Thanks for your kind reply
Excellent présentation and easy to undresfand. BRAVO