Categories
Visualizing trends in Google Sheets is one of the very important tasks you can ever undertake.
Why?
It offers important insights into whether key metrics are on a growing or declining path. With this you can easily find out whether main data points are down or up-trending.
Some of the tested and proven charts for visualizing general trends in your data are:
The visualization designs (mentioned above) are amazingly easy to interpret. Besides, you can use these charts to create compelling data stories.
Google Sheets is a popular data visualization choice among professionals and business owners worldwide. However, the freemium application involves a lot of steps for creating trend analysis-oriented graphs, such as Control Chart.
Yes, you read that right.
It turns out you can download and install a particular add-in to access ready-made and visually stunning trend-oriented visualization designs, such as Run and Control Charts.
In this blog post, you’ll learn the following:
Before addressing the main theme of the blog, we’ll address the following question: what is a Control Chart?
Definition: The Control Chart is one of the best charts you can use to examine how a process changes over time. In this chart, data is plotted in time order to analyze the data.
The chart has:
These lines are determined using data gathered.
By comparing current data to these lines, you can easily draw conclusions about whether the process variation is consistent (in control) or unpredictable (out of control) and affected by special causes of variation.
The control chart is among the seven basic quality control tools and is used in many industries.
Control Charts are best used in pairs. The top chart monitors the average or the centering of the distribution of data from the process. And the bottom chart monitors the range or the width of the distribution.
The control chart was invented by Walter A. Shewhart working for Bell Labs in the 1920s.
The company’s engineers had been seeking to improve the reliability of their telephony transmission systems. Because amplifiers and other equipment had to be buried underground, there was a stronger business need to reduce the frequency of failures and repairs.
By 1923, engineers had already realized the importance of reducing variation in a manufacturing process.
They had realized that continual process adjustment in reaction to non-conformance increased variation and degraded quality. Shewhart framed the problem in terms of common and special causes of variation.
In 1924, Shewhart wrote an internal memo introducing the Control Chart as a tool for distinguishing between the two.
Keep reading because, in the coming section, we’ll address the differences between Control Chart vs. Run Chart. Also, we’ll address the following question: what does a Control Chart tell you?
You don’t want to miss this.
A Control Chart begins with a time series graph.
A central line (X) is added as a visual reference for detecting shifts or trends – this is also referred to as the process location.
Upper and lower control limits (UCL and LCL) are computed from available data and placed equidistant from the central line. This is also referred to as process dispersion.
In the coming section, we’ll address the following question: when should you use a Control Chart?
So, what are the benefits of a Control Chart?
The Control Chart is incredibly easy to read and interpret. Besides, the chart is incredibly easy to plot if you have the right visualization tool.
You can leverage this chart to make reliable settings, especially in the manufacturing sector.
If the process is in control, all the points will fall between the control limits. Any observations outside the limits, or systematic patterns within, suggest the introduction of a new (and likely unanticipated) source of variation, known as a special-cause variation.
Since increased variation means increased quality costs, a Control Chart “signaling” the presence of a special cause requires immediate investigation.
This makes the control limits very important decision aids. The control limits provide information about the process behavior and have no relationship to any specification targets or engineering tolerance.
The purpose of a Control Chart is to allow simple detection of events that are indicative of an increase in process variability.
The visualization design can help you find answers to the following:
In the coming section, we’ll address the differences between Control Chart vs. Run Chart. Also, we’ll cover the limitations of Control Charts.
The chart violates the likelihood principle. However, the principle is itself controversial.
Supporters of Control Charts further argue that it’s impossible to specify a likelihood function for a process not in statistical control, especially where knowledge about the cause system of the process is weak.
Some data visualization experts critique the use of average run lengths for comparing Control Chart performance. And this is because the average usually follows a geometric distribution, which has high variability and difficulties.
The visualization design shows common cause and special cause variations. Common cause variations are normal and usually do not require intervention, while special cause variations require attention.
It may show you a false special cause variation, which wastes your time and resources.
Before unpacking the differences between Control Chart vs. Run Chart, we’ll address the following question: what is a Run Chart?
A Run Chart is a graph you can use to display trends and patterns in your data. You can leverage this visualization design to monitor data over time to detect trends, shifts, or cycles.
Also, you can use the graph to compare a measure before and after the implementation of the solution to measure impact.
The chart displays observed data in a time sequence. Often, the data displayed represent some aspect of the output or performance of a manufacturing or other business process. It is therefore a form of a Line Chart.
Seven or eight values in succession above or below the median line are regarded as a shift. And it indicates the dramatic change in a process.
The runs are all the data points below the median line, as shown above.
Clusters are aggregated data points on either side of the median line.
A trend occurs when seven or more consecutive points are increasing or decreasing on either side of the median line. So, when should you use a Run Chart?
Run Charts are an easy way to graphically summarize a univariate data set. The chart can help you to detect trends and outliers present in your data
Use the chart if your goal is to uncover hidden anomalies and errors in a process.
Check out more scenarios for using the chart.
In the coming section, we’ll cover the benefits of a Run Chart.
You can use a Run Chart to:
So, what are the limitations of Run Charts?
In the coming section, we’ll address the core of the blog: The difference between a Control Chart vs. Run Chart.
Control charts monitor the stability of the process.
In other words, it displays output variables over time and sees the results consistently fall within the control limits. Both upper and control limits are well defined in this graph.
On the other hand, a Run Chart focuses on displaying the shifts and trends in your data. Also, unlike a Control chart, it does not show the stability of a process.
And this is because it lacks control limits to map the upper and lower range.
In the coming section, we’ll focus primarily on the Control Chart. Also, you’ll discover how to access this chart in Google Sheets. You don’t want to miss this.
Google Sheets is a trusted data visualization tool because it’s familiar and has been there for decades.
But the spreadsheet application lacks ready-made Control Charts.
We understand switching tools is not an easy task.
Therefore, we’re not advocating you ditch Google Sheets in favor of other expensive data visualization tools.
There’s an easy-to-use and amazingly affordable visualization tool that comes as an add-in you can easily install in your Google Sheets to access ready-made Control Charts. The tool is called ChartExpo.
So, what is ChartExpo?
ChartExpo is an incredibly intuitive add-on you can easily install in your Google Sheets without watching hours of YouTube tutorials.
With many ready-to-go visualizations, ChartExpo turns your complex, raw data into compelling chart renderings that tell data stories in real time.
In the coming section, we’ll take you through how to install & use ChartExpo to create control chart and other charts in Google Sheets.
You don’t want to miss this!
This section will use a Control Chart to visualize the tabular data below.
| Weeks | Quantity |
| Week-1 | 121 |
| Week-2 | 131 |
| Week-3 | 132 |
| Week-4 | 125 |
| Week-5 | 141 |
| Week-6 | 126 |
| Week-7 | 126 |
| Week-8 | 130 |
| Week-9 | 143 |
| Week-10 | 146 |
| Week-11 | 148 |
| Week-12 | 151 |
| Week-13 | 152 |
| Week-14 | 156 |
| Week-15 | 157 |
| Week-16 | 155 |
| Week-17 | 157 |
| Week-18 | 143 |
| Week-19 | 131 |
| Week-20 | 127 |
To install the ChartExpo, add-on for Google Sheets, click this link.
Run Charts are an easy way to summarize a univariate data set graphically. The chart can help you to detect trends and outliers present in your data
Use the chart if your goal is to uncover hidden anomalies and errors in a process.
You can use a Run Chart to:
Visualizing trends in Google Sheets is one of the critical tasks you can ever undertake.
It provides significant insights into whether crucial metrics are on a growth or decline path. You can easily know whether key data points are down or up-trending.
Some of the tested and proven charts for visualizing general trends in your data are Control and Run Charts. The visualization designs (mentioned above) are straightforward to interpret. Besides, you can use these charts to create compelling data stories.
Google Sheets is a popular data visualization choice among professionals and business owners worldwide. However, the freemium application lacks trend analysis-oriented charts.
So, what’s the solution?
We recommend you install third-party apps, such as ChartExpo, to access ready-to-use Control Charts.
ChartExpo is an add-on for Google Sheets with insightful and ready-to-go Control Charts. You don’t need programming or coding skills to use ChartExpo.
Sign up for a 7-day free trial today to access ready-made Control Charts that are easy to interpret and visually appealing to your target audience.
How much did you enjoy this article?
Click to learn what a Sankey Diagram is and how to make a Sankey Diagram in a few clicks without any coding. You will also learn about the benefits and components of the Sankey Chart.
Click to learn how to analyze questionnaire data. Also, we’ll address the following question: what is questionnaire data?
Click to discover top 6 Data Visualizations Examples. You will also learn how to create top 6 data visualizations using few examples without any coding in a few clicks.
