Associated Learning OutcomesLO1.Demonstrate proficiency in utilizing R and Excel to effectively explore and describe data sets in the life sciences.LO2.Evaluate and interpret...

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Associated Learning Outcomes

  • LO1.

    Demonstrate proficiency in utilizing R and Excel to effectively explore and describe data sets in the life sciences.

  • LO2.

    Evaluate and interpret different types of data in the natural sciences by visualising probability distributions and calculating probabilities using RStudio and Excel.

  • LO5.

    Articulate statistical and modelling results clearly and convincingly in both written reports and oral presentations, working effectively as an individual and collaboratively in a team, showcasing the ability to convey complex information to varied audiences.


  • Your project must be neatly produced in a singleQuarto Document, output as HTML format.

  • If you cannot render to HTML, copy code, output, figures, tables to aMicrosoft Word Document, create your neatly presented report and submit.

  • You willsubmityour final HTML/Word/PDF doc file to the Turn-it-in tool in Canvas via theProject 1 assignmentlink.

We have also provided aproject templatefolder to help you out with setting up your first project. This can be accessed


Download here

. The template provided is a project folder with relevant quarto documents as well as some examples of how you can make nicely presented documents

Links to an external site.

. You will have to unzip the folder to access the project folder. Double click on the Rproj file in the project folder to open the project. If you are having issues with rendering your document, please let us know ASAP as we can assist you with making it work or we can provide alternative ways of creating your final document!

Things to think about when using AI

  • You must take 100% responsibility for any submissions you make, and you must acknowledge how you have used generative AI, if you have used it.

  • Your assessment submission must not be taken directly from the output of these tools. It needs to be put into your own words.

  • You will create a journal with (i) the name(s) of the AI tool(s)/forums you used, (ii) a brief description of what purpose(s) you used them for, and (iii) a brief description of how you used the tool(s) (e.g. what prompts did you provide, what questions did you ask)

  • DATA:

Answered 1 days AfterMar 29, 2024

Answer To: Associated Learning OutcomesLO1.Demonstrate proficiency in utilizing R and Excel to...

Bhaumik answered on Mar 31 2024
9 Votes
1) Dataset Description
The dataset "Foster_Kitten" contains a comprehensive set of attributes pertaining to the fostering and adoption process of kittens. Let's delve into the description and potential insights derived from these attributes.
Fostering Stage:
· Breed, Colour, Age_weeks, Weight: These attributes provide essential information about the kitten's physical characteristics, such as breed, colour, age, and weight, which can influence fostering and adoption decisions.
· Gender: Understanding the gender distribution of kittens can be crucial for various analyses, including behavioural studies and adoption rates.
· Foster_Reasons, Animal_Source: These attributes shed light on the reasons for foste
ring and the source of the kitten, which could affect its initial health and behaviour.
Fostering Environment:
· Attributes from F_1 to F_24 capture various aspects of the foster environment, including interactions with other animals, exposure to different stimuli, and reactions to specific situations. Analyzing these attributes can help identify factors contributing to the kitten's socialization, comfort, and overall well-being during the fostering period.
Adoption Stage:
· Attributes from A_1 to A_45 pertain to the adopter's observations and experiences after taking the kitten into their household. These attributes cover a wide range of behaviours, health indicators, and environmental factors affecting the kitten's adjustment and happiness in its new home.
Analysis and Insights:
1. Fostering Success Factors: Analyzing foster reasons, interactions with other animals, and environmental stimuli can identify factors contributing to successful fostering outcomes, such as socialization and adaptability.
2. Adoption Predictors: Attributes related to the kitten's behavior, health, and interactions in its new home can serve as predictors of successful adoptions. For instance, behaviors like friendliness, playfulness, and adaptability may positively influence adoption rates.
3. Health and Well-being: Monitoring health indicators such as weight, appetite, grooming habits, and instances of illness or distress can provide insights into the overall health and well-being of fostered and adopted kittens.
4. Behavioural Patterns: Attributes related to behaviors like aggression, nervousness, activity levels, and sociability can help identify common behavioral patterns among kittens during both fostering and adoption stages.
5. Environmental Factors: Understanding the impact of environmental factors such as household noise levels, the presence of other pets, and interactions with visitors on the kitten's behavior and well-being can inform recommendations for optimal fostering and adoption environments.
The "Foster_Kitten" dataset encapsulates a rich array of attributes spanning the fostering and adoption journey of kittens. By analyzing these attributes, stakeholders can gain valuable insights into factors influencing fostering success, adoption outcomes, and the overall health and well-being of kittens transitioning into new homes. Leveraging this information can facilitate the development of strategies to enhance the fostering and adoption process, ultimately improving the lives of fostered and adopted kittens.
2) Subset the data to several (3 -5) variables and investigate the data using statistical and graphical summaries.
3) Write a short report about your findings and why they are important.
Short Report: Analysis of Fostered and Adopted Kittens
1. Age Distribution:
The distribution of age in weeks among the kittens shows a varied range, indicating that kittens of different ages were fostered or adopted. This suggests that there is a need for foster care and adoption services for kittens of various ages.
2. Weight Distribution:
The weight distribution of the kittens varies, indicating that there is diversity in the sizes of fostered and adopted kittens. This highlights the importance of considering the nutritional and health needs of kittens of different weights during foster care and adoption processes.
3. Gender Distribution:
The count of kittens by gender shows a distribution between male and female kittens. Understanding the gender distribution can help in designing targeted adoption campaigns and providing appropriate care based on gender-specific needs.
4. Foster Reasons:
The count of kittens by foster reasons provides insights into why kittens are placed into foster care. Common reasons include being too young for adoption, neonatal care, and protective custody. Understanding these reasons helps in providing specialized care and support for kittens with specific needs.
5. Adoption Status:
The count of kittens by adoption status reveals the outcomes of the fostering process. It indicates the number of kittens that settled well in their adopted households. Monitoring adoption status helps in assessing the effectiveness of foster care programs and improving the adoption process for better outcomes.
Importance of Findings:
The findings from this analysis are important for several reasons:
· Animal Welfare: Understanding the demographics and outcomes of fostered and adopted kittens is crucial for ensuring their welfare and well-being.
· Resource Allocation: Insights into age, weight, gender distribution, and reasons for fostering help in allocating resources effectively to meet the diverse needs of kittens in foster care.
· Improving Processes: Monitoring adoption status and reasons for fostering enables organizations to identify areas for improvement in foster care and adoption processes.
· Targeted Interventions: Gender-specific care and tailored adoption campaigns can be developed based on the gender distribution of kittens.
In conclusion, the analysis of fostered and adopted kittens provides valuable insights for improving foster care programs, enhancing adoption outcomes, and ultimately ensuring the well-being of kittens in need of care and support.
4) Describe the types of data present in your subset of variables; e.g. Numerical (Continuous, Discrete) or Categorical (Binary, Nominal, Ordinal)
Let's describe the types of data present in the subset of variables we analyzed:
1. Age_Weeks:
· Type: Numerical (Continuous)
· Description: Represents the age of the kittens in weeks. It is a continuous variable as it can take any value within a range and can be measured with precision.
2. Weight:
· Type: Numerical (Continuous)
· Description: Represents the weight of the kittens. It is also a continuous variable as it can take any value within a range and can be measured with precision.
3. Gender:
· Type: Categorical (Binary)
· Description: Represents the gender of the kittens. It is a binary categorical variable as it has two categories: Male and Female.
4. Foster_Reasons:
· Type: Categorical (Nominal)
· Description: Represents the reasons for fostering the kittens. It is a nominal categorical variable as it represents distinct categories without any inherent order or ranking.
5. A_1:
· Type: Categorical (Ordinal)
· Description: Represents the adoption status of the kittens. It is an ordinal categorical variable as it represents categories with a specific order or ranking: settled well in the...

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