MATH1324: Applied Analytics - Descriptive Statistics and Visualisation - Mathematics Assignment Help

Assignment Task:

Overview 

This assignment is simple. You are asked to work on a project and data is provided. This is your opportunity to demonstrate all that you have learnt so far in this course. You will be awarded (with marks) the clearer you demonstrate your skills. This isn’t about showing off. You won’t be rewarded for applying advanced statistical analysis outside the course. That’s not what this course is about. This course is about asking and answering interesting questions about the world using the fundamentals of statistics. 

This investigation will seek to understand if there is any statistical significant relationship between a person’s chest diameter (che.di) and height (hgt). To do this, you are going to use the Body Measurements Dataset (bdims.csv) which is located under Google Drive -> Data Repository. 

This assignment is worth 20% and must be uploaded to the Assignment 3 submission by 24/05/2020. 

Submission Instructions The report must be slides uploaded as a PDF with relevant code showing. You can also use other format to provide slideshow. Presentations are limited (maximum) to 20 slides. The presentation must be composed of the following sections. You can add more if your wish, but you must include these sections as a minimum. 

1. Presentation title and group/individual details [Plain text]: You can add the title of your presentation and student(s) details by updating the “title” and “author” entries at the top.

2. Introduction [Plain text]: A good introduction provides a brief background to the problem, defines important terms, and leads to a strong rationale. 3. Problem Statement [Plain text]: State the overall problem/question driving the investigation. 

Summarise how you will use statistics to solve the problem or answer the question.

4. Data [Plain text]: Explain how you pre-processed it for analysis. There should be enough detail here so that someone else could replicate your data collection. List and explain the important variables. You decide, it’s your project! You just need to explain and justify your choices.

5. Descriptive Statistics and Visualisation [Plain text & R code & Output]: Summarise the important variables in your investigation. Use visualisation to highlight interesting features of the data and tell the overall story. Explain how you dealt with data issues (if any), e.g. missing data and outliers.

6. Hypothesis Testing [Plain text & R code & Output]: Apply appropriate hypothesis tests for your investigation. Ensure you state the hypotheses and check any assumptions. Report the appropriate values and interpret the results.

7. Discussion [Plain text]: Discuss the major findings of your investigation. Discuss any strengths and limitations. Propose directions for future investigations. This is a good place to re-state your findings as a final conclusion. What is the one take home message the reader should leave with? 8. References [Plain text]: Provide a list of any references you use in the presentation. 

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