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R4BABS.Rproj

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 Version: 1.0
+ProjectId: bd585bbe-c101-4d0f-938a-c160d7d2b873
 
 RestoreWorkspace: Default
 SaveWorkspace: Default

r4babs2/r4babs2.qmd

@@ -4,11 +4,20 @@ toc: true
 toc-location: right
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+# Welcome!
 
+Welcome to an exciting six-week journey into data analysis with R! 
+In this part of the module, we’ll explore key concepts that are essential
+for any budding bioscientist, including **the logic of hypothesis testing**, 
+a foundation for making informed decisions based on data and 
+**Statistical models** for analysing patterns and relationships across multiple 
+variables.
 
-# Introduction
+This module builds on your skills from BABS1 step-by-step, helping you gain 
+confidence in applying statistical tools to real-world bioscience problems. 
+By the end, you’ll have a solid understanding of how to analyse data to go with
+your existing skills in summarising and plotting it.
 
-This is the second of the four BABS modules. Over six weeks you will learn about the logic of hypothesis testing, confidence intervals, what is meant by a statistical model, two-sample tests and one- and two-way analysis of variance (ANOVA).
 
 ## Module Learning Objectives
 
@@ -24,39 +33,66 @@ The BABS2 Module Learning outcomes that relate to the Data Analysis in R content
 
 # How this part of the module is organised
 
-A key feature of this module is that you really do learn as you go along and you should not need to revise very much. To support this learning, every week is structured in the same way with contact time and well-guided independent study to prepare you for the contact time and consolidate what you have learned. 
+This module is designed to help you learn as you go — meaning you won’t need to 
+spend hours revising. Instead, you’ll build skills gradually and steadily 
+through a structured weekly schedule that combines contact time and guided 
+independent study. The goal is to make learning manageable, effective, and 
+enjoyable.
 
 Each week has:
 
--   An overview on the "About" page which gives the Learning Objectives, a topic summary and the instructions for the week. You should read this first. 
+-   An "About" page which gives a topic summary, the Learning Objectives,  and 
+    the instructions for the week. You should read this first.
+
+-   Some independent study on the "Prepare!" page to help you get ready for 
+    the workshop. This will be reading from the course book ([Computational 
+    Analysis for Bioscientists](https://3mmarand.github.io/comp4biosci/)), 
+    watching a video, or doing some coding or some set up. The preparation is 
+    designed to take about 30-45 minutes on average. To make it more fun and 
+    more productive, study with other people.
+
+-   A two-hour workshop using R to apply concepts you are learning. We will 
+    usually start with a demonstration of an example from the "Prepare!" tasks.
+    You will spend most of the workshop diving into exercises, and building on 
+    previous weeks’ skills while being introduced to new concepts. Anything you 
+    have not done before is explained and guided but you will also have the 
+    opportunity to solve problems using using the skills gained in previous 
+    workshops on your own or with others. I often remind 
+    you to take care of future you by making notes so you can look up your 
+    previous work but you can also search the 
+    [R4BABS](https://3mmarand.github.io/R4BABS/) site (search is top right). 
+
+-   The "Consolidate!" page has independent exercises to reinforce what you’re
+    learning. These are similar to the workshop activities but with less 
+    guidance to encourage independent thinking. Occasionally, there will also 
+    be some reading. It is designed to take about 30-45 mins on average but may
+    be quicker if you understood the workshop very well or slower if you need 
+    to revisit parts.
+
+# Tips for Learning R:
+
+Learning R is a bit like learning a new language, picking up a musical
+instrument, or mastering a sport — you can’t cram it all at once. Consistency 
+is key. Even small, regular practice sessions are more effective than trying 
+to do it all in one go.
+
+-   a little bit of engagement and practice is always better than none, so 
+    celebrate bit effort!
+
+-   if you fall behind, don’t stress. Just pick up where you left off — there’s 
+    no need to skip ahead. It is fine to work on a previous week’s workshop!
 
--   Some independent study on the "Prepare!" page to prepare you for the workshop. This will be reading from the course book ([Computational Analysis for Bioscientists](https://3mmarand.github.io/comp4biosci/)),  watching a video, or doing some coding or set up. It is designed to take about 30-45 mins on average. You will most likely learn best if you can find people to study with. 
-
--   A two-hour workshop using R. This will usually start with me doing a short demonstration of one or more of the examples that were in "Prepare!" but you will spend most of the session going through some exercises. Anything you have not done before is explained and guided but you will also have to use the skills gained in previous workshops. I often remind you to take care of future you by making notes so you can look up your previous work but you can also search the [R4BABS](https://3mmarand.github.io/R4BABS/) site (search is top right). Talking to other people in the workshop about the exercises and working together will really help you understand more. There will be plenty of help from me and my demonstrators.
-
--   Some independent study on the "Consolidate!" page to give you more practice. The exercises are usually similar to those in the workshop but with less guidance. Occasionally, there will be reading to do. It is designed to take about 30-45 mins on average but may be quicker if you understood the workshop very well or slower if you need to revisit the workshop. 
-
-Learning Data Analysis in R is like learning to speak a new language or play an instrument or a technical sport - you can't really rush it or cram for it. You need regular practice. 
-
--   a little bit of engagement and practice is always better than none
-
--   if you get behind, just pick up where you left off rather than jumping in. It is fine to work on a previous week's workshop
 
 # Content
 
 ## The logic of hypothesis testing and CIs
 
-
-##  Introduction to statistical models: Single regression
-
+## Introduction to statistical models: Single regression
 
 ## Two-sample tests
 
-
 ## One-way ANOVA and Kruskal-Wallis
 
-
 ## Two-way ANOVA
 
-
-## Association: Correlation and Contingency
+## Association: Correlation and Contingency

update_notes.txt

@@ -52,21 +52,27 @@ Add a folder for each strand which contains strand specific content.
 Group only access to relevant folder  done by SAS
 
 VLE iframe
-Week 1 Data Analysis in R for BABS 2
 
+<h2 style="color:MediumSeaGreen;">Read an Overview of R for BABS 2 (below) <a href="https://3mmarand.github.io/R4BABS/r4babs2/r4babs2.html" target="_blank">or open page on external site</a></h2>
+<iframe src="https://3mmarand.github.io/R4BABS/r4babs2/r4babs2.html" allow="fullscreen"  width="800" height="800"></iframe>
 
-<h2 style="color:MediumSeaGreen;">Overview  <a href="https://3mmarand.github.io/R4BABS/r4babs2/week-6/overview.html" target="_blank">Direct link</a></h2>
-<iframe src="https://3mmarand.github.io/R4BABS/r4babs2/week-6/overview.html" title="Overview" allow="fullscreen"  width="800" height="600"></iframe>
 
 
-<h2 style="color:MediumSeaGreen;">Independent Study to do before the workshop  <a href="https://3mmarand.github.io/R4BABS/r4babs2/week-6/study_before_workshop.html" target="_blank">Direct link</a></h2>
-<iframe src="https://3mmarand.github.io/R4BABS/r4babs2/week-6/study_before_workshop.html" title="Prepare" allow="fullscreen"  width="800" height="400"></iframe>
+<h2 style="color:MediumSeaGreen;">Read an overview of Week 5 (below) <a href="https://3mmarand.github.io/R4BABS/r4babs2/week-6/overview.html" target="_blank">or open page on external site</a></h2>
+<iframe src="https://3mmarand.github.io/R4BABS/r4babs2/week-6/overview.html" allow="fullscreen"  width="800" height="800"></iframe>
 
-<h2 style="color:MediumSeaGreen;">Workshop material  <a href="https://3mmarand.github.io/R4BABS/r4babs2/week-6/workshop.html" target="_blank">Direct link</a></h2>
-<iframe src="https://3mmarand.github.io/R4BABS/r4babs2/week-6/workshop.html" title="Workshop" allow="fullscreen"  width="800" height="400"></iframe>
 
-<h2 style="color:MediumSeaGreen;">Independent Study to do after the workshop  <a href="https://3mmarand.github.io/R4BABS/r4babs2/week-6/study_after_workshop.html" target="_blank">Direct link</a></h2>
-<iframe src="https://3mmarand.github.io/R4BABS/r4babs2/week-6/study_after_workshop.html" title="Consolidation" allow="fullscreen"  width="800" height="400"></iframe>
+<h2 style="color:MediumSeaGreen;">Do this independent study (below) <a href="https://3mmarand.github.io/R4BABS/r4babs2/week-6/study_before_workshop.html" target="_blank">or open page on external site</a></h2>
+<iframe src="https://3mmarand.github.io/R4BABS/r4babs2/week-6/study_before_workshop.html" allow="fullscreen"  width="800" height="800"></iframe>
+
+
+<h2 style="color:MediumSeaGreen;">Attend the workshop (material below) <a href="https://3mmarand.github.io/R4BABS/r4babs2/week-6/workshop.html" target="_blank">or open page on external site</a></h2>
+<iframe src="https://3mmarand.github.io/R4BABS/r4babs2/week-6/workshop.html" allow="fullscreen"  width="800" height="800"></iframe>
+
+
+
+<h2 style="color:MediumSeaGreen;">Do this independent study following the workshop to consolidate your learning (below) <a href="https://3mmarand.github.io/R4BABS/r4babs2/week-6/study_after_workshop.html" target="_blank">or open page on external site</a></h2>
+<iframe src="https://3mmarand.github.io/R4BABS/r4babs2/week-6/study_after_workshop.html" allow="fullscreen"  width="800" height="800"></iframe>
 
 
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