# How do you do seasonal index in Excel?

## How do you do seasonal index in Excel?

Enter the following formula into cell C2: “=B2 / B\$15” omitting the quotation marks. This will divide the actual sales value by the average sales value, giving a seasonal index value.

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## How do you forecast seasonal index?

Seasonal indexing is the process of calculating the high’s and low’s of each time period into an index. This is done by finding an average for an entire set of data that includes the same number of matching periods, then dividing the individual period average into that total average.

How do you forecast in Excel?

Create a forecast

1. In a worksheet, enter two data series that correspond to each other:
2. Select both data series.
3. On the Data tab, in the Forecast group, click Forecast Sheet.
4. In the Create Forecast Worksheet box, pick either a line chart or a column chart for the visual representation of the forecast.

How do I forecast historical data in Excel?

Follow the steps below to use this feature.

1. Select the data that contains timeline series and values.
2. Go to Data > Forecast > Forecast Sheet.
3. Choose a chart type (we recommend using a line or column chart).
4. Pick an end date for forecasting.
5. Click the Create.

### How do you forecast regression in Excel?

Linear regression equation using Excel Chart: Just create the scatter chart or line chart for Actual sales data and add a linear regression trend line and check the Display Equation on the chart and Display R-squired value on the chart. Now Equation and R-squired value will be available on the chart.

### How do I do regression analysis in Excel?

To run the regression, arrange your data in columns as seen below. Click on the “Data” menu, and then choose the “Data Analysis” tab. You will now see a window listing the various statistical tests that Excel can perform. Scroll down to find the regression option and click “OK”.

How do you do regression forecasting?

The general procedure for using regression to make good predictions is the following:

1. Research the subject-area so you can build on the work of others.
2. Collect data for the relevant variables.
3. Specify and assess your regression model.
4. If you have a model that adequately fits the data, use it to make predictions.