I'm trying to understand the example presented in Appendix C here
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6481149/
Equation C1 is clear to me.
But in Equation C2 they use the mean values.
Such mean values are clear to me in the case of categorical variables for example 1.548 is the mean value of the Sex variable (as shown in the Table 3). Please correct me if I'm wrong.
But in numerical variables I don't understand which mean values are they using. For example for the Age variable they use 3.768, if I understand right, that value is the log of the mean age, should be log(44.15)=1.64. Instead the used value is 3.768.
Please could anybody clarify where does this value come from?
In statistics log often means the natural logarithm, sometimes denoted ln. The four values they take the logarithms of are:
Variable
Reported Mean
ln(Mean)
Reported
Age
44.15
3.788
3.768
BMI
25.61
3.243
3.230
BP Syst
138.6
4.932
4.913
Pulse Rate
75.61
4.326
4.311
The calculated values are not exactly equal to the reported values. But it looks close enough that this is probably the calculation they used. Without the data and/or code they used it's hard to say why the results are different. The study mentions excluding 130 participants because of ethics protections. So, perhaps one table was calculated using a slightly different group of participants than the other table?
I apologize if the title is a bit vague. I am trying to create a calculator that takes into account how much "scrap" I have, how much is needed to resmelt it, and how many bars recieved.
Currently using:
(=if((amtOwned/qtyToSmelt)<1,,rounddown((amtOwned/qtyToSmelt)*barsMade))
Table and Formula
The problem I am having is you MUST have the QTY to Smelt. But the value returned includes partial quantities.
Ex. 125 Bottle Caps should equal 4 Bars total. Yet it returns 5.
How can i make the formula only account for increments of the bars recieved?
Thank you for any help, again i apologize if this isn't that clear. Im not exactly sure how to express my need in this situation.
I have tried messing around with the syntax and where every argument sits, even this formula is the most recent iteration of what i thought would be needed.
EDIT: I have tried using the TRUNC function and this seems to be working as I need it to. The formula now is:
=TRUNC((AMTowned/AMTneeded),0)*barsRecieved
=TRUNC((136/50),0)*2 This is returning 2 bars instead of 3. Which is exactly what I need.
It appears this is working by truncating the number first then multiplying it. So, 1.5 becomes 1 before being multiplied. This was my guess after doing more research. I had been searching for a while before I posted this but am glad to have learned what I have in searching for this.
There is a tool for auditing formulas. To see it go to Formulas > Evaluate Formula.
So here is you formula =IF((E3/C3)<1,,ROUNDDOWN((E3/C3)*D3,0))
Have you tried the calculation on your regular calculator? To me it is doing what you would expect. (125/50)*2 = 5
I have a problematic table, which is interconnected and goes out of memory often, but I've limited it to show 50 items, but now want to limit it to show only lines that one column calculated. The calculation - one price minus another one. I need to limit the lines so that the % or the value is less than 0 (meaning everything with -% or -<0 is acceptable).
Using a calculated dimension does not let me do an if function to accomplish this. The deduction does not work for some reason.
Any help?
I just edited the formula to "=if(dimension='-' or dimension='0', null(), dimension)". So the kicker was actually setting this all to "null()" so the "Suppress When Value Is Null" recognizes things to null.
This actually solves my problem in a different way, however the goal is the same. This skips the values where a calculation is impossible due to lack from one source.
[UPDATE Jun-3rd-2017]: I figured out exactly what I needed. I just made the calculation on the script side and now a calculated dimension is actually restricting all of the values by the calculated dimension as was intended.
What I have attempted:
AVERAGEIF(B11:V11,">+MEDIAN(B11:V11)")
What I am trying to do:
I would like to take the average of the upper half of given data. Elaborating more. I would like to find a formula that will allow me to remove a given lower fence of outliers and dissect the data then given to me. I would greatly prefer to maintain this formula within one cell "not grabbing different results from formulas within multiple cells".
Update:
Following through I found the solution.. I think.
One thing I should have explained further:
The data coming in replicating a typical sqrt function.
What I wanted to achieve is to capture the mean of the "plateau" of the data.
The equation I used was:
=AVERAGEIF(B3:B62,(">"&+TRIMMEAN(B3:B62,0.8)),B3:B62)
This was something I just copied and pasted. of course "B3" and "B62" are significant only for my application.
My rough explanation of the equation:
TRIMMEAN will limit the AVERAGE to the top 20%(">")(0.8) of the data selected. So for my application, this SHOULD give me a rough mean of the "plateau" of the data i would like to find the mean for.
This formula calculates the Median() of the range, then AverageIf() uses the median and only grabs values that are greater than or equal to >= the median ~ giving you the average of the 'top-half' of your values.
AVERAGEIF(A1:A10,">="&MEDIAN(A1:A10))
Hope this help!
I'm sure this is the kind of problem other have solved many times before.
A group of people are going to do measurements (Home energy usage to be exact).
All of them will do that at different times and in different intervals.
So what I'll get from each person is a set of {date, value} pairs where there are dates missing in the set.
What I need is a complete set of {date, value} pairs where for each date withing the range a value is known (either measured or calculated).
I expect that a simple linear interpolation would suffice for this project.
If I assume that it must be done in Excel.
What is the best way to interpolate in such a dataset (so I have a value for every day) ?
Thanks.
NOTE: When these datasets are complete I'll determine the slope (i.e. usage per day) and from that we can start doing home-to-home comparisons.
ADDITIONAL INFO After first few suggestions:
I do not want to manually figure out where the holes are in my measurement set (too many incomplete measurement sets!!).
I'm looking for something (existing) automatic to do that for me.
So if my input is
{2009-06-01, 10}
{2009-06-03, 20}
{2009-06-06, 110}
Then I expect to automatically get
{2009-06-01, 10}
{2009-06-02, 15}
{2009-06-03, 20}
{2009-06-04, 50}
{2009-06-05, 80}
{2009-06-06, 110}
Yes, I can write software that does this. I am just hoping that someone already has a "ready to run" software (Excel) feature for this (rather generic) problem.
I came across this and was reluctant to use an add-in because it makes it tough to share the sheet with people who don't have the add-in installed.
My officemate designed a clean formula that is relatively compact (at the expensive of using a bit of magic).
Things to note:
The formula works by:
using the MATCH function to find the row in the inputs range just before the value being searched for (e.g. 3 is the value just before 3.5)
using OFFSETs to select the square of that line and the next (in light purple)
using FORECAST to build a linear interpolation using just those two points, and getting the result
This formula cannot do extrapolations; make sure that your search value is between the endpoints (I do this in the example below by having extreme values).
Not sure if this is too complicated for folks; but it had the benefit of being very portable (and simpler than many alternate solutions).
If you want to copy-paste the formula, it is:
=FORECAST(F3,OFFSET(inputs,MATCH(F3,inputs)-1,1,2,1),OFFSET(inputs,MATCH(F3,inputs)-1,0,2,1
(inputs being a named range)
There are two functions, LINEST and TREND, that you can try to see which gives you the better results. They both take sets of known Xs and Ys along with a new X value, and calculate a new Y value. The difference is that LINEST does a simple linear regression, while TREND will first try to find a curve that fits your data before doing the regression.
The easiest way to do it probably is as follows:
Download Excel add-on here: XlXtrFun™ Extra Functions for Microsoft Excel
Use function intepolate().
=Interpolate($A$1:$A$3,$B$1:$B$3,D1,FALSE,FALSE)
Columns A and B should contain your input, and column G should contain all your date values. Formula goes into the column E.
A nice graphical way to see how well your interpolated results fit:
Take your date,value pairs and graph them using the XY chart in Excel (not the Line chart). Right-click on the resulting line on the graph and click 'Add trendline'. There are lots of different options to choose which type of curve fitting is used. Then you can go to the properties of the newly created trendline and display the equation and the R-squared value.
Make sure that when you format the trendline Equation label, you set the numerical format to have a high degree of precision, so that all of the significant digits of the equation constants are displayed.
The answer above by YGA doesn't handle end of range cases where the desired X value is the same as the reference range's X value. Using the example given by YGA, the excel formula would return #DIV/0! error if an interpolated value at 9999 was asked for. This is obviously part of the reason why YGA added the extreme endpoints of 9999 and -9999 to the input data range, and then assumes that all forecasted values are between these two numbers. If such padding is undesired or not possible, another way to avoid a #DIV/0! error is to check for an exact input value match using the following formula:
=IF(ISNA(MATCH(F3,inputs,0)),FORECAST(F3,OFFSET(inputs,MATCH(F3,inputs)-1,1,2,1),OFFSET(inputs,MATCH(F3,inputs)-1,0,2,1)),OFFSET(inputs,MATCH(F3,inputs)-1,1,1,1))
where F3 is the value where interpolated results are wanted.
Note: I would have just added this as a comment to the original YGA post, but I don't have enough reputation points yet.
alternatively.
=INDEX(yVals,MATCH(J7,xVals,1))+(J7-MATCH(J7,xVals,1))*(INDEX(yVals,MATCH(J7,xVals,1)+1)-INDEX(yVals,MATCH(J7,xVals,1)))/(INDEX(xVals,MATCH(J7,xVals,1)+1)-MATCH(J7,xVals,1))
where j7 is the x value.
xvals is range of x values
yvals is range of y values
easier to put this into code.
You can find out which formula fits best your data, using Excel's "trend line" feature. Using that formula, you can calculate y for any x
Create linear scatter (XY) for it (Insert => Scatter);
Create Polynominal or Moving Average trend line, check "Display Equation on
chart" (right-click on series => Add Trend Line);
Copy the equation into cell and replace x's with your desired x value
On screenshot below A12:A16 holds x's, B12:B16 holds y's, and C12 contains formula that calculates y for any x.
I first posted an answer here, but later found this question