software

I have a data set with volume numbers at certain price points. I want to use
the data to determine what might be the outcome at different prices. For
instance:

At $.99 per lb, the average lb sold is 100,000 lbs.
At $1.29, per lb, lbs sold is about 77,000 lbs.
And on. What I am trying to figure out is how much I could expect to sell at
price points where I have no history of sales. Please tell me there is an
easy, uncomplicated way to do this. I am not a statistician.

I'm not a stat person either. But I put .99 in B1 and .01 in C1. In B2
=B1 $C$1 and pulled down until I had 1.29. Row 31.

In E1 I entered 100,000. In F1 742, (approx the value of 100000 - 77000
divided by 31)

In E2 =E1-$F$1 and pulled down to row 31. I adjusted F1 until E31 equalled
77,020.

Just a linear chart that says at 1.13 = 89,276, at 1.05 = 95,405, etc.
Basically 766 pound per penny.

HTH
Regards,
Howard

quot;Price Elasticityquot; lt;Price gt; wrote in
message ...
gt;I have a data set with volume numbers at certain price points. I want to
gt;use
gt; the data to determine what might be the outcome at different prices. For
gt; instance:
gt;
gt; At $.99 per lb, the average lb sold is 100,000 lbs.
gt; At $1.29, per lb, lbs sold is about 77,000 lbs.
gt; And on. What I am trying to figure out is how much I could expect to sell
gt; at
gt; price points where I have no history of sales. Please tell me there is an
gt; easy, uncomplicated way to do this. I am not a statistician.
L. Howard Kittle wrote...
gt;I'm not a stat person either. But I put .99 in B1 and .01 in C1. In B2
gt;=B1 $C$1 and pulled down until I had 1.29. Row 31.

So far, so good, but arguably cleaner to make the B2 formula =B1 0.01,
then fill down.

gt;In E1 I entered 100,000. In F1 742, (approx the value of 100000 - 77000
gt;divided by 31)
....

Now not so good. Just enter 100000 in C1 and 77000 in C31, select
C1:C31, run the menu command Edit gt; Fill gt; Series, select Linear as
Type and click OK.

But there are no guarantees the demand curve is even approximately
linear.Hi Harlan,

gt;But there are no guarantees the demand curve is even approximately
linear

I guessed that was the case but didn't know. What I do quot;kinda guaranteequot;
is, if you are a non pro at Excel and lurk about in this news group and pay
attention, you will pick up tips and gain knowledge. Which I just did with
your critique of my offered solution. Never heard of quot;linearquot; fill until
now. And the .01 in a separate cell does not make sense in retrospect. I
did that because I had some vague thought of changing the increment for the
B column. Point well taken.

Thanks Harlan,
Regards,
Howard

quot;Harlan Grovequot; gt; wrote in message ups.com...
gt; L. Howard Kittle wrote...
gt;gt;I'm not a stat person either. But I put .99 in B1 and .01 in C1. In B2
gt;gt;=B1 $C$1 and pulled down until I had 1.29. Row 31.
gt;
gt; So far, so good, but arguably cleaner to make the B2 formula =B1 0.01,
gt; then fill down.
gt;
gt;gt;In E1 I entered 100,000. In F1 742, (approx the value of 100000 - 77000
gt;gt;divided by 31)
gt; ...
gt;
gt; Now not so good. Just enter 100000 in C1 and 77000 in C31, select
gt; C1:C31, run the menu command Edit gt; Fill gt; Series, select Linear as
gt; Type and click OK.
gt;
gt; But there are no guarantees the demand curve is even approximately
gt; linear.
gt;