2. Trendlines in charts
A trend line is a straight line connecting
multiple points on a chart.
A trend is a movement in a particular
direction
The magnitude of the slope of a trend line,
or steepness, indicates the strength of the
trend.
Trendlines can be used to forecast future !
3. Creating trendline in excel
Select the graph and
right click
Select add Trend line
4. Trendline types
A window opens with types
of trend line to select from 6
Options
Select the default option
for trend line – Linear
Click OK
6. Formatting trendline
Right click on the trend line to
format it.
Select style, color and weight
of your choice
7. Options - Name
-Trendline Name
- You can give custom name for
your trendline such as .. Sales
trend… etc.
8. Options - Forecast
by using this forecast Option
you can extend the trend line
forward or backward to the
number of periods as desired
Here I selected 6 periods
(Months - in this case) forward
9. Options - Forecast
You can Observe that the trendline got
extended in to the future by 6 periods
This denotes if this trend continues, the
sales of XYZ territory are likely to be like this
10. Options – Display equation and R2 Value
by clicking “display equation
on Chart” and display r-Squared
value on chart, you will be able
to display them on the graph
Next slide explains them
You can Set Intercept to any
value by clicking it and adding
value (0 is default).
As this Option is not used often in simple trend
lines , explanation is beyond the scope of this
slide set.
11. equation
This is the equation generated by excel that
holds the mathematical relationship of Sales and
months.
This equation will be unique to each data set
This equation can be used to compute sales of
any future month
to put it simply , here “y” denotes the sale
(which is on Y axis) and x denotes the month
So lets compute 13th month (Jan-2011 in this
case) projection, using this equation
y= ((17.311)*13)+296.39 that equals 521.43
So the likely sales projection for 13th month is
521.43
12. R squared Value
This is the R_squared Value for this trendline.
This value denotes the reliability of the sales
projections.
R squared value will range between 0 and 1
If the R squared value is 1, then the trend is
most predictable and reliable.
The reliability of trendline goes up if the R-
squared value is nearest to 1
Let us see the next example to understand it
better.
13. R squared Value = 1
Here the R_squared Value is 1.
Just take a look at the sales progress.
With every passing month, this territory is
adding $100 to the previous month.
So, going by the trend, you can be almost sure,
that the 13th month sales are .
Remember, Trend lines and Forecasts means you
are presuming the existing market conditions are
not going to change radically.
14. Six types of trend lines
1. Linear
2. Logarithmic
3. Polynomial
4. Power
5. Exponential
6. Moving
Average
15. Best fit Trendline
We have learnt that if R2 Value is near to 1, the
reliability of trendline is better.
So, now we need to use a trend line from the five
available trend lines in excel menu to arrive at the
most appropriate one to ensure that our forecast is
most reliable.
The other trendline left out is Moving average for
which ,you will neither get the equation nor the R2
value.
Simplest way to find the best fit trendline is to check
every trend line’s R2 Value and use the trendline
with highest R2 value ( Which is nearest to 1- out of 5
16. Rule of thumb to use type of Trendline
1. Linear trendline : use it if data values are
increasing or decreasing at a steady rate.
2. Logarithmic trendline : Useful when the rate
of change in the data increases or decreases
quickly and then levels out.
3. Polynomial trendline : Used when there are
data fluctuations like the sales following
seasonal trends
17. Rule of thumb to use type of Trendline
4. Power trendline : Use with data that has
values that increase at specific rate at regular
intervals.
5. Exponential trendline : Use when data
values increase or decrease rates that are
constantly increasing.
6. Moving average trendline : Use it when
uneven fluctuations are in data values