This article will illustrate how to calculate the standard error of regression slope in Excel. The standard error is the standard deviation of an evaluation. Generally, the standard error of the regression slope line refers to how certain variables are scattered from the mean value. The average variance between your observed values and the regression line is the standard error of the regression slope.
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2 Effective Ways to Calculate Standard Error of Regression Slope in Excel
In this article, we will demonstrate 2 effective ways to calculate the standard error of regression slope in Excel. The smaller the value of standard error will be, the closer our values will be to the regression line. For both methods of this article, we will use the same data set.
1. Calculate Standard Error of Regression Slope with Scatter Chart in Excel
First and foremost, calculate the standard error of regression slope in Excel with a scatter chart. For instance, we want to calculate standard error from the following dataset. The dataset contains the price and quantity of some products.
Let’s see the steps to calculate the standard error.
- To begin with, select cell (B4:C9).
- In addition, go to the Insert tab.
- Then, click on the ‘Insert Scatter (X, Y) or Bubble Chart’ Icon. Select the first scatter chart.
- A chart like the following image will appear. We can see data points on the chart.
- Next, right-click on any data point and select the option ‘Add Trendline’.
- The above action will insert a trendline in the graph.
- Furthermore, click on the trendline.
- Go to the Trendline Options.
- Check the options ‘Display Equation on chart’ and ‘Display R-squared value on chart’.
- Moreover, select the chart.
- Then, go to Chart Design > Add Chart Element > Axis Title.
- Set titles of axis using the option ‘Primary Horizontal’ and ‘Primary Vertical’.
- After setting the axis names our table will look like the following image.
- Afterward, following the trendline equation insert the below formula in cell D5:
=4.2202*B5 + 122.98
- Press Enter.
- So, we get the predicted price from the trendline in cell D5.
- Now, drag the Fill Handle tool from cell D5 to D9.
- After that, insert the following formula in cell E5:
- Press Enter.
- So, we get the standard error for the first point in cell E5.
- Finally, drag the Fill Handle tool from cell E5 to E9.
- As a result, we get standard errors of regression slope for all the data points.
Read More: How to Find Slope of Trendline in Excel (2 Easy Methods)
2. Excel LINEST Function to Calculate Standard Error Along with Uncertainty of Regression Slope
Another method to calculate the standard error of regression slope is to use the LINEST function. The LINEST function in excel illustrates the relation between independent variables and multiple dependent variables. It returns the result in array form. We will predict the deviation of the Y value from the regression line using the uncertainty of the regression slope. We will use the following dataset to illustrate this method.
Let’s see the steps to perform this method.
- Firstly, select cell (C11:D12).
- Secondly, type the following formula in cell C11:
- Don’t press Enter. Hit Ctrl + Shift + Enter since it is an array formula.
- The above command will give results like the following image.
- Thirdly, like method-1 we will construct a formula with the value of Slope and Y-Intercept. Insert that formula in cell D5:
- Press Enter.
- So, we get the predicted price in cell D5.
- Furthermore, drag the Fill Handle tool from cell D5 to D9.
- Next, to calculate the standard error insert the following formula in cell E5:
- Now, press Enter.
- Again, drag the Fill Handle tool from cell E5 to E10.
- Lastly, we get standard errors of regression slope for all the data points.
Read More: How to Find Uncertainty of Slope in Excel (with Easy Steps)
In conclusion, this tutorial is a complete guide to calculating the standard error of regression slope in Excel. To put your skills to the test, use the practice worksheet that comes with this article. Please leave a comment in the box below if you have any questions. We’ll try to reply to you as soon as possible. In the future, keep an eye on our website for more fascinating Microsoft Excel solutions.
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