Divide the monthly average by the overall monthly average to get the Seasonal Index for each month. Divide the sales amount for that month by the seasonal index for that month to deseasonalize your data.
Deseasonalized data can be used to investigate the trend and any lingering irregularities. You should keep the original data for future modelling reasons because information is lost during the seasonal adjustment process.
Choose the data set that includes the timeline series and values.
Select Data > Forecast > Forecast Sheet from the drop-down menu.
Decide on a chart type (we recommend using a line or column chart).
Set a deadline for predicting.
Press the Create button.
You can use historical time-based data to make a forecast if you have it. When you make a prediction, Excel creates a new worksheet with a table of historical and anticipated values as well as a chart to visualise the information.
The following is the difference between TREND and FORECAST in Excel: The FORECAST function can only forecast future values using current values as a starting point. Both present and future trends can be calculated using the TREND function.
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Pratik Meshram
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where is assignment PDF
Gourav Parmar
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Hey Provide me the Practice File
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Gitesh Saini
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This aap very helpful for human
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Rishu Baghel
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sir, can you provide us some table for practice?
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shams faishal
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please provide your excel file so it will be easy to learn fast
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Pintu Kumar
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improve video quality, because its excel file and the pixel is not good.
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Juboraj Juboraj
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Explain details & easy to understand.
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MD Ayaz Rain
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powerBI use a data Analysis course in hindi
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Omkar Jitendra Shinde
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It is great course
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Vaibhav Magar
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I would suggest Absolute reference in 13:30 for the calculation of percentage
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