.. _r_tutorials_assignments:

Computer Assignments and Tutorials
-------------------------------------------------

Overview
~~~~~~~~

The course includes six computer assignments that progressively build your R skills and statistical analysis capabilities. Each assignment focuses on specific statistical techniques and is accompanied by a detailed tutorial. **All assignments use the AppRating dataset as the primary data source**, supplemented with additional datasets for practice and demonstration.

.. important::
   **Dataset Requirements**: 
   
   - Download the appropriate **AppRating dataset** for your session (Fall or Winter) at the start of the course
   - This same dataset is used throughout ALL six assignments
   - Additional tutorial datasets are provided for specific examples
   - See :ref:`r_datasets` for all download links

Assignment Structure by Session
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

**Regular Session (Fall/Spring)**

Six separate assignments, each focusing on distinct statistical concepts:

- CA1: Introduction to R and data exploration
- CA2: Graphical and numerical summaries  
- CA3: Basic hypothesis testing and subsetting
- CA4: Two-sample procedures
- CA5: One-way ANOVA
- CA6: Simple linear regression

**Winter Session (Accelerated)**

Five assignments with CA1 and CA2 combined:

.. note::
   Winter Session combines the first two assignments and renumbers the rest:
   
   - Assignment 1: Combined CA1 & CA2 content
   - Assignment 2: Basic hypothesis testing (originally CA3)
   - Assignment 3: Two-sample procedures (originally CA4)
   - Assignment 4: One-way ANOVA (originally CA5)
   - Assignment 5: Simple linear regression (originally CA6)

Assignment Tutorials (Links)
-------------------------------------------------

- **Computer Assignment 1 Tutorial** — Data Exploration and Statistical Analysis:
  `CA1 Tutorial <https://treese41528.github.io/STAT350/Computer_Assignment_Tutorials/Computer_Assignment_1_Tutorial.html>`_
- **Computer Assignment 2 Tutorial** — Subsetting and Basic Statistical Inference:
  `CA2 Tutorial <https://treese41528.github.io/STAT350/Computer_Assignment_Tutorials/Computer_Assignment_2_Graphical_and_Numerical_Summaries_Tutorial.html>`_
- **Computer Assignment 3 Tutorial** — Two-sample Procedures:
  `CA3 Tutorial <https://treese41528.github.io/STAT350/Computer_Assignment_Tutorials/Computer_Assignment_3_BasicHypothesisTesting_and_subsetting_Tutorial.html>`_
- **Computer Assignment 4 Tutorial** — Two-sample procedures:
  `CA4 Tutorial <https://treese41528.github.io/STAT350/Computer_Assignment_Tutorials/Computer_Assignment_4_TwoSampleProcedures_Tutorial.html>`_
- **Computer Assignment 5 Tutorial** — One-way ANOVA:
  `CA5 Tutorial <https://treese41528.github.io/STAT350/Computer_Assignment_Tutorials/Computer_Assignment_5_ANOVA_Tutorial.html>`_
- **Computer Assignment 6 Tutorial** — Simple linear regression:
  `CA6 Tutorial <https://treese41528.github.io/STAT350/Computer_Assignment_Tutorials/Computer_Assignment_6_SimpleLinearRegression_Tutorial.html>`_

**Winter Session**

- **Computer Assignment 1 Tutorial** — Intro & basics:
  `CA1 Tutorial <https://treese41528.github.io/STAT350/Winter/Computer_Assignment_Tutorials/Computer_Assignment_1_Tutorial_Data_Exploration_and_Statistical_Analysis.html>`_
- **Computer Assignment 2 Tutorial** — Subsetting & basic hypothesis testing:
  `CA2 Tutorial <https://treese41528.github.io/STAT350/Winter/Computer_Assignment_Tutorials/Computer_Assignment_2_BasicHypothesisTesting_and_subsetting_Tutorial.html>`_
- **Computer Assignment 3 Tutorial** — Two-sample procedures:
  `CA3 Tutorial <https://treese41528.github.io/STAT350/Winter/Computer_Assignment_Tutorials/Computer_Assignment_3_TwoSampleProcedures_Tutorial.html>`_
- **Computer Assignment 4 Tutorial** — One-way ANOVA:
  `CA4 Tutorial <https://treese41528.github.io/STAT350/Winter/Computer_Assignment_Tutorials/Computer_Assignment_4_ANOVA_Tutorial.html>`_
- **Computer Assignment 5 Tutorial** — Simple linear regression:
  `CA5 Tutorial <https://treese41528.github.io/STAT350/Winter/Computer_Assignment_Tutorials/Computer_Assignment_5_SimpleLinearRegression_Tutorial.html>`_

Course Pipeline (At a Glance)
-------------------------------------------------

1. **Import**: ``read.csv`` → **inspect** with ``head``, ``str``, ``summary``.
2. **Validate & clean**: missing data (``is.na``, ``complete.cases``), types (``as.numeric``, ``factor``), quick checks (``length``, ``nrow``, ``unique``).
3. **Explore**: core summaries (``mean``, ``median``, ``sd``, ``quantile``, ``IQR``), plots (``ggplot2`` histograms/boxplots).
4. **Model**: one/two-sample t; ANOVA; SLR via ``lm``; compute p-values/intervals; **diagnostics** (residual plots, QQ).
5. **Report**: figures/tables (``ggplot2``, ``knitr::kable`` + ``kableExtra``), short text with context.