For example, if the supplies expenses for January, February, and March of 2017 represent 5.2%, 6.8%, and 9.4%, respectively, of total supplies for 2017, then those same ratios would be used to distribute the 2018 total supplies budget to January, February, and March of 2018 (and so on for each month). Because most companies experience seasonal variations in revenue and expense line items, the budget projections should therefore be seasonalised by summing the monthly projected 2018 budget values and redistributing them using 2017's seasonality. As illustrated in the trendline chart shown in Image 3, this linear-regression method produces results that follow a straight-line path, resulting in no data seasonality. Image 4: Exporting income statements from Dynamics GP to ExcelДЈ. We will compensate for this minor formatting issue by adjusting some of our later calculations accordingly.) (You might notice that Dynamics GP creates income statements in which the credit balances, such as revenue line items, are displayed as negative numbers, which is not typically how accountants display those amounts. Our regression-based budgeting process starts by exporting four years' worth of monthly income statement data from Dynamics GP to Microsoft Excel (something virtually every accounting system allows users to do), as suggested in Image 4. For this example, the budgeting process is broken into eight steps, as follows.ДЎ. Now that we've covered a basic understanding of regression using the Fill Handle tool, let's put this tool in action using the detailed sample data included in Microsoft's Dynamics GP accounting system.

These two SLOPE/INTERCEPT and FORECAST function calculations derive the same answer as does Excel's Fill Handle, which proves the Fill Handle's accuracy, so you can have confidence in using this tool to create your own budget data. The resulting formula =F9+F8*F5 produces the product 1,176,995, which matches the product produced by the Fill Handle method in cell F7 of Image 2.ДЇor further proof of the Fill Handle's accuracy, we can also write the formula =FORECAST(F5,B6:E6,B5:E5) to produce the same projected 1,176,955 value, based on the same data used above. Then, in cell F10, we calculated the projected value for period 5 by adding the Slope (cell F8) and the Intercept (cell F9) multiplied by 5 (cell F5) to derive the fifth period amount. In cells F8 and F9, we entered the formulas =SLOPE(B6:E6,B5:E5) and =INTERCEPT(B6:E6,B5:E5), respectively. Starting with the same sales numbers used above, we replaced the date labels in cells B5 through F5 with the numbers 1 through 4 (because these numbered data points are essential for the SLOPE and INTERCEPT formulas to work properly). To prove the Fill Handle's accuracy, these same projected numbers can also be calculated mathematically using Excel's SLOPE and INTERCEPT functions, as follows. Image 3: Excel scatter chart and trendline This scatter chart and trendline visually suggest how Excel's Fill Handle tool works - and how the actual historical data are used to project the future data points. The red data points correspond to the future values calculated in cells F7 through H7 in Image 2.

To depict the process further, I have extended the linear line and added data points at intervals equivalent to the actual data intervals (as illustrated by the red dotted line, data points, and interval arrows in Image 3). This resulting blue trendline represents the one true linear line that dissects the data points in such a manner that when all the distances from each data point to the trend line are squared and added together, they produce the least amount (hence, the least-squares method). Next, right-click any one of the blue data points, and from the resulting pop-up menu, select Add Trendline (the blue dotted line in Image 3). To do this, highlight the actual data cells (cells B7 through E7 in this example) and create a scatter chart by selecting Insert, Insert Scatter (X,Y) or Bubble Chart, Scatter, as pictured in blue data points in Image 3. These regression calculations can be demonstrated visually using Excel's trendline chart.

Linear regression excel 2017