# Scattergraph Method: What it Means, How it Works, Example

Then draw the line alongside the visual spot, the line will use to estimate the fixed and variable cost. Fixed cost is the exact point where the line meets Y-axis, it represents the cost when production zero. The total variable is calculated by subtracting fixed costs from the total mixed cost. Scatter graph method is a graphical technique of separating fixed and variable components of mixed cost by plotting activity level along x-axis and corresponding total cost (i.e. mixed cost) along y-axis. A regression line is then drawn on the graph by visual inspection. The line thus drawn is used to estimate the total fixed cost and variable cost per unit.

By plotting the relevant data, the fixed and variable cost components can be determined from specific points on the graph. For example, the $380,000 in production costs incurred in April may be higher than normal because several production machines broke down resulting in costly repairs. Or perhaps several key employees left the company, resulting in higher than normal labor costs for the month because the remaining employees were paid overtime. Cost accountants will often throw out the high and low points for this reason and use the next highest and lowest points to perform this analysis. Note that we are identifying the high and low activity levels rather than the high and low dollar levels—choosing the high and low dollar levels can result in incorrect high and low points. Plot activity level (i.e. number of units, labor hours etc.) along x-axis and total mixed cost along y-axis.

If this section of the line is used to estimate the value of a variable given a value of the other, then this is known as extrapolation. An estimated line of best fit can be used to estimate the value of one variable given a value of the other within scattergraph method the range of the highest and lowest data values. Overplotting occurs when there are too many data points to plot, which results in the overlapping of different data points. It can make relationship identification between variables challenging.

- Each row of the table will become a single dot in the plot with position according to the column values.
- Use the scatter graph to separate the fixed and variable costs.
- A scatter plot with point size based on a third variable actually goes by a distinct name, the bubble chart.
- This can be convenient when the geographic context is useful for drawing particular insights and can be combined with other third-variable encodings like point size and color.

Scatter plots are used to observe relationships between variables. From the scattergraph method, the company can estimate that for each unit produced, the production cost increases by $9 (variable cost). No matter the production level, there’s a consistent cost of $500 (fixed cost). Based on the graph above, the line of best fit crosses the y-axis at approximately $12,000, hence total fixed costs is equal to $12,000. The method is also not useful when there is little correlation between the costs incurred and the related activity level because projecting costs into the future is difficult.

In reviewing Figure 5.4, you will notice that this approach only considers the high and low activity levels in establishing an estimate of fixed and variable costs. The high and low data points may not represent the data set as a whole, and using these points can result in distorted estimates. The scatter graph method is used to segregate mixed costs and is more accurate than the high-low method.

## A Complete Guide to Funnel Charts

As we know that the student has an average of 6 hours of sleep, we label this value on the horizontal axis. Below is a scatter graph that represents the number of hours of sleep per night of 10 students and the score they achieved in a spelling test. An energy company was researching the monthly bills of a street of homes in December.

The data points or dots, which appear on a scatter plot, represent the individual values of each of those data points and also allow pattern identification when looking at the data holistically. If a causal link needs to be established, then further analysis to control or account for other potential variables effects needs to be performed, in order to rule out other possible explanations. https://personal-accounting.org/ A scatter plot can also be useful for identifying other patterns in data. We can divide data points into groups based on how closely sets of points cluster together. Scatter plots can also show if there are any unexpected gaps in the data and if there are any outlier points. This can be useful if we want to segment the data into different parts, like in the development of user personas.

## Understanding the Scattergraph Method

Sometimes bivariate data can appear to have 3 variables and not just two. For example, the table below shows information from a small independent electronics shop. They have recorded the year, the number of TVs sold, and the amount of money spent on advertising. As the table has 3 rows of data it may appear to have 3 variables. Here the line of best fit has been extended so that it stretches beyond the data set (it is no longer surrounded by plotted points).

## Cost Function

The example scatter plot above shows the diameters and heights for a sample of fictional trees. Each dot represents a single tree; each point’s horizontal position indicates that tree’s diameter (in centimeters) and the vertical position indicates that tree’s height (in meters). From the plot, we can see a generally tight positive correlation between a tree’s diameter and its height. We can also observe an outlier point, a tree that has a much larger diameter than the others. This tree appears fairly short for its girth, which might warrant further investigation. Review this section to be sure you understand

variable, fixed, and mixed costs.

If the third variable we want to add to a scatter plot indicates timestamps, then one chart type we could choose is the connected scatter plot. Rather than modify the form of the points to indicate date, we use line segments to connect observations in order. This can make it easier to see how the two main variables not only relate to one another, but how that relationship changes over time. If the horizontal axis also corresponds with time, then all of the line segments will consistently connect points from left to right, and we have a basic line chart. Regression analysis tends to be most accurate because it provides a cost equation that best fits the line to the data points.

The aim is to draw a straight line in the direction of the correlation shown, with points distributed either side of the line as equally as possible along its length. Your line may also pass directly through a number of points. Outliers can occur for different reasons so it is important to look at the context of the graph to determine possible reasons for them. An outlier is a piece of data which does not fit with the rest of the data set. This website is using a security service to protect itself from online attacks.

When a scatter plot is used to look at a predictive or correlational relationship between variables, it is common to add a trend line to the plot showing the mathematically best fit to the data. This can provide an additional signal as to how strong the relationship between the two variables is, and if there are any unusual points that are affecting the computation of the trend line. Sometimes there is a strong relationship between data and other times the relationship is weak. You can see this visually on a scatter graph by observing how close the plots are together in forming a line.