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On this page

  • Honesty Pledge
  • Format and mode of submission
  • Style and organisation
  • Packages
  • Question 1
  • Question 2: Bullfrog Occupancy and Common Reed Invasion
  • Question 3: Growth Curves for Sitka Spruce Trees in 1988 and 1989
  • Question 4: Frog Dehydration Experiment on Three Substrate Types
  • Research Project: Intercity Distances and Biodiversity Conservation
    • Goal
    • How You’ll Do It
    • Project Breakdown
  • Submission instructions
  • Edit this page
  • Report an issue

BCB744: Summative End-of-Intro-R Task

Author
Affiliation

Smit, A. J.

University of the Western Cape

Published

Invalid Date

Honesty Pledge

This assignment requires that you work as an individual and not share your code, results, or discussion with your peers. Penalties and disciplinary action will apply if you are found cheating.

Acknowledgement of the Pledge

Copy the statement, below, into your document and replace the underscores with your name acknowledging adherence to the UWC’s Honesty Pledge.

I, ____________, hereby state that I have not communicated with or gained information in any way from my peers and that all work is my own.

Format and mode of submission

This Assignment requires submission as both a Quarto (.qmd) file and the knitted .html product. You are welcome to copy any text from here to use as headers or other pieces of informative explanation to use in your Assignment.

Style and organisation

As part of the assessment, we will look for a variety of features, including, but not limited to the following:

  • Content:
    • Questions answered in order
    • A written explanation of approach included for each question
    • Appropriate formatting of text, for example, fonts not larger than necessary, headings used properly, etc. Be sensible and tasteful.
  • Code formatting:
    • Use Tidyverse code and style conventions
    • No more than ~80 characters of code per line (pay particular attention to the comments)
    • Application of R code conventions, e.g. spaces around <-, after #, after ,, etc.
    • New line for each dplyr function (lines end in %>%) or ggplot layer (lines end in +)
    • Proper indentation of pipes and ggplot() layers
    • All chunks labelled without spaces
    • No unwanted / commented out code left behind in the document
  • Figures:
    • Sensible use of themes / colours
    • Publication quality
    • Informative and complete titles, axes labels, legends, etc.
    • No redundant features or aesthetics

Packages

For this assignment, you will have to install the AICcmodavg and MASS packages. The former package contains the datasets bullfrog and dry.frog, and the latter has the Sitka and Sitka89 datasets.

Question 1

Insert Task G which can be found here.

Question 2: Bullfrog Occupancy and Common Reed Invasion

AICcmodavg::bullfrog

Create a tidy dataframe from the bullfrog data.

Question 3: Growth Curves for Sitka Spruce Trees in 1988 and 1989

MASS::Sitka and MASS::Sitka89

Provide an analysis of the growth curves for Sitka spruce trees in 1988 and 1989. Provide graphical support for the hypotheses that i) ozone affects the growth of Sitka spruce trees, and ii) the growth of Sitka spruce trees is affected by the year of measurement.

Question 4: Frog Dehydration Experiment on Three Substrate Types

AICcmodavg::dry.frog

α. Provide a 200 word synopsis of the purpose of this study.

b. Create new columns in the dataframe showing:

  • the final mass;
  • the percent mass lost; and
  • the percent mass lost as a function of the initial mass of each frog.

c. Provide the R code that would have resulted in the data in the variables cent_initial_mass and cent_Air.

d. An analysis of the factors responsible for dehydration rates in frogs. In your analysis, consider the effects substrate type, initial mass, air temperature, and wind.

e. Provide a brief discussion of your findings.

The deadline for submitting Q.1-3 of Task G is 23:59 1 Mar 2024.

Research Project: Intercity Distances and Biodiversity Conservation

Goal

This project explores the potential relationship between the distances between major cities and the state of biodiversity conservation within five countries: South Africa, Australia, the USA, the UK, and Brazil.

How You’ll Do It

1. Find Data: Use freely available resources to gather two types of data:

  • Intercity distances for the top 20 most populous cities in each country.
  • Biodiversity metrics for each country. These could be direct measures (e.g., species richness) or proxy measures (e.g., percentage of protected areas).

2. Analyse Relationships: Calculate mean intercity distances for each country. Graphically present your biodiversity metrics. Then, look for patterns between the city distances and biodiversity state for each country.

3. Discuss Your Findings: Explain the significance of your results in the context of biodiversity conservation. Can you see a connection between how far apart cities are and the health of a country’s ecosystems?

Project Breakdown

Introduction

  • Briefly explain why urbanisation and city placement might impact biodiversity.
  • Clearly state your research question and the approach you’ll take to answer it.

Methods

  • List your data sources (provide links!).
  • Describe how you calculated intercity distances (straight-line, road networks, etc.).
  • Explain your choice of biodiversity metrics.
  • Outline your analytical steps (software, statistical tests, etc.).

Results

  • Present your results in clear tables and graphs, including:
    • table of mean intercity distances for each country
    • visualisations of your chosen biodiversity metrics for each country
    • graphs comparing intercity distances with biodiversity metrics
  • Ensure all figures and tables have descriptive titles and labels.

Discussion

  • Do your results suggest a link between intercity distance and biodiversity? Support your claim with evidence from your analysis.
  • How do your findings compare to existing research on the subject (a small literature review is a good addition here)?
  • What are the potential limitations of your analysis?
  • Summarise your conclusions.

Tips

  • Work Together: Collaborate with a partner. Divide tasks, offer suggestions, and review each other’s work.
  • Data Wrangling: Real-world data is messy. Be prepared to clean and organise your data so it’s usable for your analysis. Show all your code!
  • R and Quarto: These tools make it easy to write, compile, and share your report. If you’re unfamiliar with them, look for online tutorials and examples.
  • Submission: Create a well-formatted HTML document using Quarto. Zip your entire project folder along with the document for submission, making sure everything renders when the HTML file is opened.

Let me know if you have any questions about specific parts of these instructions!

The deadline for submitting the Research Project of Task G is 08:00 25 Mar 2024.

Submission instructions

Submission instructions

Submit your .qmd and .html files wherein you provide answers to these Questions by no later than 1 March 2024 at 23:59 for Questions 1-4, and 08:00 25 Mar 2024 for the Research Project.

Label the files as follows:

  • BCB744_<first_name>_<last_name>_Final.qmd, and

  • BCB744_<first_name>_<last_name>_Final.html

(the < and > must be omitted as they are used in the example as field indicators only).

Failing to follow these instructions carefully, precisely, and thoroughly will cause you to lose marks, which could cause a significant drop in your score as formatting counts for 15% of the final mark (out of 100%).

Submit your Tasks on the Google Form when ready.

Reuse

CC BY-NC-SA 4.0

Citation

BibTeX citation:
@online{smit,_a._j.,
  author = {Smit, A. J.,},
  title = {BCB744: {Summative} {End-of-Intro-R} {Task}},
  date = {},
  url = {http://tangledbank.netlify.app/assessments/BCB744_Summative_1_2024.html},
  langid = {en}
}
For attribution, please cite this work as:
Smit, A. J. BCB744: Summative End-of-Intro-R Task. http://tangledbank.netlify.app/assessments/BCB744_Summative_1_2024.html.
Source Code
---
title: "BCB744: Summative End-of-Intro-R Task"
subtile: "Final CA Task and Exam Preparation"
date: "Due: 1 and 25 March 2024 at 23:59"
format:
  html:
    code-fold: false
    toc-title: "On this page"
    standalone: true
    toc-location: right
    page-layout: full
    embed-resources: false
number-sections: false
---

## Honesty Pledge

**This assignment requires that you work as an individual and not share
your code, results, or discussion with your peers. Penalties and
disciplinary action will apply if you are found cheating.**

::: callout-note
## Acknowledgement of the Pledge

Copy the statement, below, into your document and replace the
underscores with your name acknowledging adherence to the UWC's Honesty
Pledge.

**I, \_\_\_\_\_\_\_\_\_\_\_\_, hereby state that I have not communicated
with or gained information in any way from my peers and that all work is
my own.**
:::

## Format and mode of submission

This Assignment requires submission as both a Quarto (.qmd) file and the
knitted .html product. You are welcome to copy any text from here to use
as headers or other pieces of informative explanation to use in your
Assignment.

## Style and organisation

As part of the assessment, we will look for a variety of features,
including, but not limited to the following:

-   Content:
    -   Questions answered in order
    -   A written explanation of approach included for each question
    -   Appropriate formatting of text, for example, fonts not larger
        than necessary, headings used properly, etc. Be sensible and
        tasteful.
-   Code formatting:
    -   Use **Tidyverse** code and [style
        conventions](https://style.tidyverse.org/)
    -   No more than \~80 characters of code per line (pay particular
        attention to the comments)
    -   Application of [R code
        conventions](http://adv-r.had.co.nz/Style.html), e.g. spaces
        around `<-`, after `#`, after `,`, etc.
    -   New line for each `dplyr` function (lines end in `%>%`) or
        `ggplot` layer (lines end in `+`)
    -   Proper indentation of pipes and `ggplot()` layers
    -   All chunks labelled without spaces
    -   No unwanted / commented out code left behind in the document
-   Figures:
    -   Sensible use of themes / colours
    -   Publication quality
    -   Informative and complete titles, axes labels, legends, etc.
    -   No redundant features or aesthetics

## Packages

For this assignment, you will have to install the **AICcmodavg** and **MASS**
packages. The former package contains the datasets `bullfrog` and `dry.frog`, and the latter has the `Sitka` and `Sitka89` datasets.

## Question 1

Insert **Task G** which can be found
[here](../BCB744/intro_r/11-tidy.html#pivot_longer).

## Question 2: Bullfrog Occupancy and Common Reed Invasion

`AICcmodavg::bullfrog`

Create a tidy dataframe from the bullfrog data.

## Question 3: Growth Curves for Sitka Spruce Trees in 1988 and 1989

`MASS::Sitka` and `MASS::Sitka89`

Provide an analysis of the growth curves for Sitka spruce trees in 1988 and 1989. Provide graphical support for the hypotheses that i) ozone affects the growth of Sitka spruce trees, and ii) the growth of Sitka spruce trees is affected by the year of measurement.

## Question 4: Frog Dehydration Experiment on Three Substrate Types

`AICcmodavg::dry.frog`

α. Provide a 200 word synopsis of the purpose of this study.

b\. Create new columns in the dataframe showing:

-   the final mass;
-   the percent mass lost; and
-   the percent mass lost as a function of the initial mass of each
    frog.

c\. Provide the R code that would have resulted in the data in the
variables `cent_initial_mass` and `cent_Air`.

d\. An analysis of the factors responsible for dehydration rates in
frogs. In your analysis, consider the effects substrate type, initial
mass, air temperature, and wind.

e\. Provide a brief discussion of your findings.

**The deadline for submitting Q.1-3 of Task G is 23:59 1 Mar 2024.**

## Research Project: Intercity Distances and Biodiversity Conservation

### Goal
This project explores the potential relationship between the distances between major cities and the state of biodiversity conservation within five countries: South Africa, Australia, the USA, the UK, and Brazil.

### How You'll Do It

**1. Find Data:** Use freely available resources to gather two types of data:

- Intercity distances for the top 20 most populous cities in each country.
- Biodiversity metrics for each country. These could be direct measures (e.g., species richness) or proxy measures (e.g., percentage of protected areas).

**2. Analyse Relationships:** Calculate mean intercity distances for each country.  Graphically present your biodiversity metrics. Then, look for patterns  between the city distances and biodiversity state for each country.

**3. Discuss Your Findings:** Explain the significance of your results in the context of biodiversity conservation. Can you see a connection between how far apart cities are and the health of a country's ecosystems?

### Project Breakdown

#### Introduction

-   Briefly explain why urbanisation and city placement might impact biodiversity.
-   Clearly state your research question and the approach you'll take to answer it.

#### Methods

-   List your data sources (provide links!).
-   Describe how you calculated intercity distances (straight-line, road networks, etc.).
-   Explain your choice of biodiversity metrics.
-   Outline your analytical steps (software, statistical tests, etc.).

#### Results

-   Present your results in clear tables and graphs, including:
    - table of mean intercity distances for each country
    - visualisations of your chosen biodiversity metrics for each country
    - graphs comparing intercity distances with biodiversity metrics
-   Ensure all figures and tables have descriptive titles and labels.

#### Discussion

-   Do your results suggest a link between intercity distance and biodiversity? Support your claim with evidence from your analysis.
-   How do your findings compare to existing research on the subject (a small literature review is a good addition here)?
-   What are the potential limitations of your analysis?
-   Summarise your conclusions.

#### Tips

-   **Work Together:** Collaborate with a partner. Divide tasks, offer suggestions, and review each other's work.
-   **Data Wrangling:** Real-world data is messy. Be prepared to clean and organise your data so it's usable for your analysis. Show all your code!
-   **R and Quarto:** These tools make it easy to write, compile, and share your report. If you're unfamiliar with them, look for online tutorials and examples.
-   **Submission:** Create a well-formatted HTML document using Quarto. Zip your entire project folder along with the document for submission, making sure everything renders when the HTML file is opened.

Let me know if you have any questions about specific parts of these instructions!

**The deadline for submitting the Research Project of Task G is 08:00 25 Mar 2024.**

## Submission instructions

::: callout-important
## Submission instructions

Submit your .qmd and .html files wherein you provide answers to these
Questions by no later than 1 March 2024 at 23:59 for Questions 1-4, and
08:00 25 Mar 2024 for the Research Project.

Label the files as follows:

-   `BCB744_<first_name>_<last_name>_Final.qmd`, and

-   `BCB744_<first_name>_<last_name>_Final.html`

(the `<` and `>` must be omitted as they are used in the example as
field indicators only).

Failing to follow these instructions carefully, precisely, and
thoroughly will cause you to lose marks, which could cause a significant
drop in your score as formatting counts for 15% of the final mark (out
of 100%).

Submit your Tasks on the Google Form when ready.
:::

© 2025, AJ Smit

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