#install.packages("downloader")
#install.packages("rafalib")

Assignment front sheet

Qualification Unit number and title
Pearson BTEC Level 4 HNC Diploma in Applied Biology/Chemistry Unit 6 Analysis of Scientific Data and Information
Student Name Assessor Name
____ Michael Hunt
Date Issued Completion Date Submitted On
22/11/2017 13/12/2017

Assignment Title: Presentation of Scientific Information

Learning Outcome Assessment Criteria In this assessment you will have the opportunity to present evidence that shows you are able to: Task no. Evidence (Page no)
1 1.1 Create a plan for the presentation of scientific information 1,4
1 1.2 Display data to scientific standards using planned methods 1,2,3
1 1.3 Carry out graphical methods of displaying scientific data 1,2,3,4

Learner Declaration

To submit this work to Moodle you are required to certify that the work submitted for this assignment is your own and that research sources are fully acknowledged. ____

Assignment Brief

Unit number and title Unit 6 Analysis of Scientific Data and Information
Qualification Pearson BTEC Level 4 HNC Diploma in Applied Biology/Chemistry
Start Date
Deadline
Assessor

Introduction

In this assignment you will explore ways of displaying data effectively for a given audience.

You are expected to use R to complete this assignment, and to submit two html files created from an R markdown file. The file will be submitted electronically to the Moodle site by the deadline. In addition you are required to publish your document to the web at RPubs.

A helpful text for this assignment can be found here

Task One

First we will set up a data frame that contains the proportion of users that use each of five different web browsers.

Run this chunk of code:

names<-c("Opera",  "Safari","Firefox","IE","Chrome") 
proportions<-c(1,9,20,26,44)
browsers<-data.frame(names,proportions)
  1. Write a command that shows the structure of the browsers data frame.
  2. How many variables are there, and how many observations?
  3. Plot this data using a pie chart, including a suitable title, with each segment labelled by the name of a browser.
  4. Plot the data as a bar chart. Each bar should be labelled with the name of a browser, the y axis should be in the range 0 to 50, and there should be horizontal grid lines with a spacing of 10.
  5. Discuss the respects in which the bar plot is a better way to display the data than the pie chart.
  6. Is either plot an improvement on a simple table of the data in this case?

Task Two

This question will use data that shows the blood pressures of individuals in two groups. Those in the treatment group had been given a new drug, while those in the control group had been given a placebo.

Run the next chunk of code.

Treatment<-c(32.14566, 34.92313, 25.51900, 33.58872, 28.01787, 26.18296, 36.38410, 23.71643)
Control<-c(44.97047, 28.25594, 36.91696, 34.86753, 47.45715, 35.90748, 35.06677, 40.09118)
dat<-data.frame(Treatment,Control)

This should have created a new data frame called ‘dat’ with two columns of data, one for the treatment group and one for the control group

  1. How many variables are there, and how many observations?
  2. Write a line of code that will display the summary statistics of each group.
  3. Plot this data in such a way as to show the centre, spread, range and the points themselves for each of the two groups, side by side. (Hint: you will use boxplot() and stripchart() to do this). The x axis should be labelled “Group” and the y-axis as “Response”

Task Three: dealing with outliers

Suppose the control group contained two outliers:

Run the following chunk of code:

Treatment<-c(32.14566, 34.92313, 25.51900, 33.58872, 28.01787, 26.18296, 36.38410, 23.71643)
Control<-c(44.97047, 28.25594, 36.91696, 34.86753, 47.45715, 35.90748,4000,8000)
datOL<-data.frame(Treatment,Control)
  1. Now show the summary statistics again for each group of data.
  2. State, with explanation,which summary statistics are robust, and which are not.
  3. Now repeat the plot of Task Two, but modify it in such a way as to display all the data clearly, despite the presence of the outliers.

Task Four: Present your report

Using the Knit button at the top of the script window in R Studio, produce from rmd document an html document.

  1. Submit this document to the Moodle site for the module by the due date for the assignment.
  2. Submit a second html version of this document, in which code chunks are not visible.
  3. Publish your document (with code chunks visible) to Rpubs. Email a url link to this document to your tutor at: Michael Hunt

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Assignment Back Sheet

Evidence Checklist Summary of Evidence Required by Student Evidence Presented
Task One 1. Code written 2. Question answrered 3. Pie chart with title and segment labels 4 Bar chart with labels and grid lines 5. Brief discussion (max 250 words) 6. Sensible comments
Task Two 1. Question answered 2. Code written 3. Suitable plot with correct labels
Task Three 1. Summary Statistics shown 2. Correct statment and explanation 3. Suitable plot that shows all data clearly
Task Four 1. Knitted html version of document submitted to Moodle (with code chunks visible), 2. Knitted html version of document submitted to Moodle (with code chunks invisible), 3. Knitted document published at RPubs

Achievement Summary

Qualification Pearson BTEC Level 4 HNC Diploma in Applied Biology/Chemistry Assessor name: Michael Hunt
Unit number and title Unit 6 Analysis of Scientific Data and Information Student name:
Criteria Reference To achieve the criteria the evidence must show that the student is able to: Achieved? (tick)
1.1 Create a plan for the presentation of scientific information
1.2 Display data to scientific standards using planned methods
1.3 Carry out graphical methods of displaying scientific data
Grading Component Grading Descriptor Contextualisation
M1 choose suitable plotting method Accurate assessment of superiority of bar plot
M2 display richness of information in data Box plot correctly done and fully labelled
M3 handle data with outliers Show understanding of difference between robust and non-robust summary statistics
M4 Present data clearly in report form rmd file knitted and presented as html file, both with code hidden and with code revealed, all formatting correct.
D1 Critically evaluate presentation methods Coherent assessment of when to use tables rather than figures
D2 combine multiple plot types in one chart Stripchart superposed on box plot.
D3 display data with outliers with clarity display data in such a way as to show outliers without hiding details of other data
D4 publish well structured and type-set report Publish report to RPubs