What Is One Variable Data Table in Google Sheets?
A one-variable data table is used in data analysis to understand how the outcome of a formula changes when we change a single input variable. Thus, you can understand how different input values impact your calculations by building a one-variable data table. It is helpful in financial modeling and forecasting, where you must understand the impact of different inputs on your output, making it easier to analyze and interpret your data. They are also useful in sensitivity analysis or scenario planning for understanding the sensitivity of your model to changes in key variables.
In the example shown below, in cell C1, we have the number of kilograms of apples sold at 14. The cost of one kilogram of apple is $4.50, so let us find the total price. We enter the formula in cell D1 as =C1 * 12. Now, we have prepared a data table. In cells A2:A6, list the kilograms. Drag the formula down from C2 to C6. Column C will automatically update to show column A’s total revenue for each unit value.
Table of contents
Key Takeaways
- A One Variable Data Table in Google Sheets is a tool used to perform the what-if analysis. Here, you can change one variable in your formula and check how it affects the results.
- Unlike Excel, Google Sheets lacks a direct Data table feature. Therefore, we must implement manual formula adjustments or scripts to achieve similar results.
- For complex what-if analyses that involve multiple variables, we must use Google Sheets’ built-in scripting language (Google Apps Script)or add-ons such as Goal Seek.
How to create a One Variable Data Table in Google Sheets?
To create a one variable data table in Google Sheets, let us look at the steps below with a simple example. One variable data table in Google Sheets allows you to test a series of values for a single input cell. It shows how they influence the result of a particular formula.
To help you better understand this feature, we are going to follow a specific example. One Variable Data Table in Google Sheets performs the what-if analysis.
Step 1: Let us consider we are investing some money in a business and have to find the return on investment. Enter the following values in your sheet. We have the formula for the final value as Return on Investment (ROI) is Investment Amount * (1 + Interest Rate).
Step 2: E2 contains the ROI formula that calculates the closing value. Here the formula is =D2 * (1 + $B$2)
Step 3: We check for values ranging from $3,000 to $7,000. Let’s create a one-variable data table. In Column D, enter the values of the initial investment to be investigated. Type our variable values in a column (D2:D7) and leave a column blank to the right to get the result.
Step 4: Type your formula in cell E2 as follows.
=D2 * (1 + $B$2)
Column E will show the total return for each investment amount based on the 7% interest rate. The formula references $B$2 to ensure the interest rate remains constant across all values.
Google Sheets lacks a direct “Data Table” feature like Excel. Therefore, users must rely on manual formula adjustments or scripts to implement them.
Examples
Using the one variable data table approach helps you visualize how a single variable affects your results, which allows for better decision-making and scenario planning. Let us look at some examples below to understand this better.
Example #1
In this simple example, you can see how changing an exam’s test score affects the overall course score. Enter the data in Google Sheets as shown below.
Step 1: Now, we can change the value of the test score ( the student’s assignment and practical mark will remain the same) and look at how this affects the final score.
Enter the marks scored by the student in Column C.
Step 2: Now, let’s examine how the formula varies when we change the test score. We enter these values in Column B from cell B5.
Step 3: Now, duplicate the required test scores to be checked from Column C5 onwards using the formula =B5 in cell C5.
Step 4: Now, enter the following one variable data table in the Google Sheets formula in cell D5 and drag it all the way down to D10.
=C5*$C$3 + $D$2*$C$2 + $D$1*$C$1
By using an absolute reference, you ensure that the formula references the weightage percentages and other scores when dragged down.
Step 5: After dragging the formula, you will get an idea of how the test score affects the final score.
In summary, the weights for assignment, practical, and test scores are given in Column C, and their corresponding scores are given in Column D.
From cell C5, we have the test scores replicated from column B5 onwards. Column C contains the calculations for the overall final test score.
This table helps you to perform a what-if analysis by varying the exam score and observing the resulting overall final score.
Example #2
In another simple one variable data table example in Google Sheets, let’s see how changing one variable affects the outcome of a formula. Here, let’s see how different interest rates affect the future value of an investment.
Step 1: Let us prepare the data table as shown below.
- Cell C1 contains the initial investment amount.
- Cell B2 onwards contains the different interest rates we wish to analyze.
- Cell B1 contains the number of number of payments to be made.
Step 2: Now, the FV formula for the final value is as follows:
=FV(rate, number_of_periods, payment_amount, [present_value], [end_or_beginning])
We enter the formula =FV(B3, $B$1,0,-$C$1,0) in cell C3.
Step 3: Press Enter and drag the Autofill handle up to cell C7.
The table below shows how changes in the interest rate impact the final value of an investment.
The above examples show how to create a one variable data table in Google Sheets; you can see how changing a variable has a profound impact on the outcome of a formula. It is beneficial for sensitivity and What-If analysis.
Another method for performing sensitivity analysis is using the Goal Seek add-on available in Google Sheets. This official add-on finds the exact values required to achieve a goal quickly.
It is how you install the Add-on.
- Click on Extensions in the Google Tab.
- Select Add-ons – Get Add-ons. It will open the marketplace.
Search for Goal Seek and install it. You can now easily use it for sensitivity or what-if analysis.
Important Things to Note
- When dragging down the formula, use the absolute reference to ensure that the formula correctly references the initial values for all variables. When dragged down, expect the variable to change.
- This concept is beneficial for financial modeling, forecasting, etc., where you try to understand the impact of different values of a single variable on your outputs.
- An important point to note is that Google Sheets does not have a “Data Table” feature like Excel. You will have to manually create such an effect by copy-pasting the formula to all cells in the data table or using array formulas or scripts for this step.
- Excel provides a built-in “What-If Analysis” feature that simplifies the creation of data tables, whereas, with Google Sheets, you have to drag the formula across a row or column.
Frequently Asked Questions (FAQs)
Yes. We can use Google Sheets to do a What-if analysis, which is similar to a sensitivity analysis in most cases. However, unlike Excel, Google Sheets doesn’t have a built-in “What-If” analysis feature. However, you can perform it in Google Sheets by manually entering the formula in the data tables and using add-ons like Goal Seek for multiple varying inputs.
Data tables can be used in data analysis as you can observe patterns and trends in your data using them. You can easily identify how changes in a single variable impact the results when you create a one variable data table. It will help you make informed decisions based on your data. It also allows you to identify optimal values for your variables to achieve the desired results. If you want to change two variables, use a two variable data table.
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