Simple linear regression (SLR) is often used in Data Science. Describe and explain what are the roles of simple linear regression in Data Science. Illustrate with a real‐world application for each of the role described. Briefly explain how they perform the roles.
Guideline: about 1000 words
First, give a brief description of Simple Linear Regression (SLR) Then explain the roles of SLR in Data Science
Find real‐world examples illustrating the roles of SLR that you described.
Credible sources: e.g. journal/conference articles, government reports…etc
Briefly explain the scenarios of the real‐world applications and the roles of SLR in the applications.
List your references under the heading ‘References’. Use Harvard style for referencing.
Prediction of Height from Metacarpal Bone Length
When anthropologists analyse human skeletal remains, an important piece of information is living stature. A method of predicting the height of an individual based on measurements of small bones in the skeletal remains is required. For a random sample of nine humans, the length of the metacarpal bone (mm) and the height (cm) were measured. Data as follow.
Guideline: about 1000 words (in report form)
Guideline for headings: Aim, introduction, method, results, interpretation, conclusions. Include all relevant plots, tables and figures (don’t forget table/figure captions)
The emphasis in PART B is good practice in performing Simple linear regression in Data Science as well as communicating results and findings effectively.
Brief guideline for the steps as follow:
What is the aim of the experiment/study? (i.e. This is the question that you are trying to find the answer to.)
What is the data science technique/method that you will use? o Perform the Exploratory Data Analysis (EDA)
Interpret the EDA with a focus on assessing if the assumptions in the technique/method are satisfied.
If justified, perform the technique/method. o Summarise your results and findings
Interpret your results and findings
Conclusions: what is the take home message