# Simple Linear Regression Plot

## Introduction

A linear regression plot allows you to visualise your variables, with more information than just the shape of the scatterplot. The linear regression plot shows you the mathematical relationship between the variables. It is important to use the linear regression plot when you have an idea about causation between your variables, rather than just a correlation.

A Simple linear regression plot is a scatter plot with a regression line that shows the general direction (trend) that a group of points (plots) seem to be heading. The plots show the relationship between a scalar dependent variable Y and an explanatory variable denoted X.

## Inputs

To illustrate the Simple Linear Regression Plot, we will run it on a dataset within South Australia

• Select South Australia as your area
• Select SA2 Chronic Disease – Modelled Estimate as your dataset, and select the following attributes:
•  Statistical Area 2 Code
•  Statistical Area 2 Name
•  Type 2 diabetes (synthetic prediction) – Rate per 100
•  Circulatory system diseases (synthetic prediction) – Rate per 100

Open the Simple Linear Regression Plot tool (Analyse → Tools → Charts → Regression Simple Linear Plot) and enter the following parameters as shown in the image below (These are also explained in more detail below the image).

[Click to Enlarge]

• Dataset Input: For this we want to select SA2 Chronic Disease – Modelled Estimate
• Dependent Variable: This is where we select the variable that we want to model, or regress on the independent variable. In this instance we choose Type 2 diabetes (synthetic prediction) – Rate per 100
• Independent Variable: This is where we select the variable that we want to test as the predictor for the dependent variable. In this instance we chooseCirculatory system diseases (synthetic prediction) – Rate per 100
• Use Variable Titles: Check this box to have “human readable names” on your output chart
• Chart Title: This is where we enter the name that we want to give the resultant plot. In this instance we choose Linear Regression Plot: Type 2 Diabetes vs Circulatory System Diseases
• Grid: Tick this if you want gridlines for your graph
• Legend: Tick this if you want to include a legend for your graph
• Greyscale: Tick this if you want your graph to be produced in greyscale; leave blank if you want it be produced in colour.

Once you have entered the parameters, click Add and Run

## Outputs

Click on the Display button on the pop-up dialogue box that appears. Your output graph should look something like the graph below

[Click to Enlarge]

Showing a positive relationship between the rate of Type 2 Diabetes and Circulatory System Diseases within South Australian SA2s