#Scatter graph creator download

LineOfBestFitReadings is returned as an array of objects with two properties “posX” and “posY”. It provides a visual representation of the overall trend in the data and allows us to make predictions and estimate values for the dependent variable based on the independent variable. This line helps us understand how one variable changes in response to changes in another variable. It is determined by minimizing the distance between the line and the observed data points. In regression analysis, the line of best fit is a straight line that summarizes the relationship between two variables. A detailed list of the properties and their definitions follows below: The JSON can be copied and used elsewhere. There will also be a JSON result payload with a number of properties that may be useful even if not used by this chart. The Y equation, showing slope and y intersect.

#Scatter graph creator download

Use the button 'Download Graph Image (.png)' in Fig 3 to download the rendered chart image to your machine.Īlong with the rendered chart, the resuls pane will have some information that may be useful beyond the scope of the rendererd chart.Use the 'Scatter point size' on 'UI' tab in fig.4 below: To increase or decrease the scatter point size. Use the 'Show energy dataset' on 'UI' tab in fig.4 below: To show or hide the dataset. Use the 'Energy -> Label, Colour and Alpha' box on 'Dataset' tab in fig.4 below: To set the Dataset Title. Use the 'Line point size' on 'UI' tab in fig.4 below: To increase or decrease the line width. Use the 'Show Line of best fit' on 'UI' tab in fig.4 below: To show or hide the dataset. Use the 'Line of Best Fit -> Label, Colour and Alpha' box on 'Dataset' tab in fig.4 below: To set the Dataset Title. Use the 'Show Legend' box on 'UI' tab in fig.4 below: To show the chart legend 4.Use the 'X Axis Label' box on 'Main Chart' tab in fig.4 below: To Set the X Axis label 3.Use the 'Y Axis Label' box on 'Main Chart' tab in fig.4 below: To Set the Y Axis label 2.

Use the 'Chart Title' box on 'Main Chart' tab in fig.4 below: To Set the chart title 1.

You can set the chart title, axis labels (leave blank to effectivly hide them), set the colours and alphas for the datasets and show or hide datsets and/or the legend. Use the 'Chart Display Settings' pane to tab to various options to customise the render chart to suit your needs. Gas kWh against Heating Degree Days over 12 month period Copy example payload to If the data points start high on the y-axis and form a descending slope, the variables have a negative correlation.Below is an example payload that you can use to test the chart:Į.g. If the data points form a rising straight line from near the origin to high y-values, the correlation could be called positive. However, the more spread out the points are, the weaker the relationship. The closer the points are clustered or closely follow a curve or line, the stronger the relationship. The closer the data points come to forming a straight line, the higher the correlation between the two variables. They can also be described as strong or weak, linear, or nonlinear. Relationships between variables can be noted as having a positive or negative correlation.

You can determine a trend or pattern in a relationship between the two variables by looking at how closely the data points cluster together or hug a line. Scatter plots often show the independent variable plotted on the horizontal axis and the dependent variable on the vertical axis. Overplotting is when data points overlap to the extent that individual dots become lost in large blobs and the graph becomes too difficult to read. You should also avoid using a scatter plot when you have lots of data points because this could cause overplotting. When not to use a scatter plot?Īvoid using a scatter plot when you have variables that are obviously not related or have no relationship. Therefore, scatter plots are best used when you have two variables that pair well together, and you want to see if there is a positive or negative correlation. When taken as a whole, the dots on a scatter plot form a pattern if there is a relationship between the two variables. Scatter plots are primarily used to see if there is a relationship between two numeric variables. The stronger the correlation, the closer the points will hug the line. If the variables are correlated, the data points will form a line or curve. It is used to show the relationship between the two variables. A scatter plot is data visualization that graphs pairs of data points for two different variables on a x-y axis.