A
C
- CALCULATE
- CALCULATETABLE
- CALENDAR
- CALENDARAUTO
- CEILING
- CHISQ.DIST
- CHISQ.DIST.RT
- CHISQ.INV
- CHISQ.INV.RT
- CLOSINGBALANCEMONTH
- CLOSINGBALANCEQUARTER
- CLOSINGBALANCEYEAR
- COALESCE
- COLUMNSTATISTICS
- COMBIN
- COMBINA
- COMBINEVALUES
- CONCATENATE
- CONCATENATEX
- CONFIDENCE.NORM
- CONFIDENCE.T
- CONTAINS
- CONTAINSROW
- CONTAINSSTRING
- CONTAINSSTRINGEXACT
- CONVERT
- COS
- COSH
- COT
- COTH
- COUNT
- COUNTA
- COUNTAX
- COUNTBLANK
- COUNTROWS
- COUNTX
- COUPDAYBS
- COUPDAYS
- COUPDAYSNC
- COUPNCD
- COUPNUM
- COUPPCD
- CROSSFILTER
- CROSSJOIN
- CUMIPMT
- CUMPRINC
- CURRENCY
- CURRENTGROUP
- CUSTOMDATA
D
E
I
N
O
P
R
S
- SAMEPERIODLASTYEAR
- SAMPLE
- SEARCH
- SECOND
- SELECTCOLUMNS
- SELECTEDMEASURE
- SELECTEDMEASUREFORMATSTRING
- SELECTEDMEASURENAME
- SELECTEDVALUE
- SIGN
- SIN
- SINH
- SLN
- SQRT
- SQRTPI
- STARTOFMONTH
- STARTOFQUARTER
- STARTOFYEAR
- STDEVX.P
- STDEVX.S
- STDEV.P
- STDEV.S
- SUBSTITUTE
- SUBSTITUTEWITHINDEX
- SUM
- SUMMARIZE
- SUMMARIZECOLUMNS
- SUMX
- SWITCH
- SYD
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U
What is the POISSON.DIST Function?
The POISSON.DIST function is a statistical function in Power BI that helps you analyze the probability of a certain number of events occurring within a given time frame. It is based on the Poisson distribution, which is a mathematical concept that models the probability of rare events happening in a specific time period.
In simpler terms, the POISSON.DIST function helps you understand the likelihood of a specific number of events happening within a given time frame. For example, you can use it to analyze the probability of a certain number of customers visiting your store in a day, or the likelihood of a certain number of defects occurring in a manufacturing process.
How Does the POISSON.DIST Function Work?
The POISSON.DIST function takes three arguments: the number of events you’re interested in, the expected number of events, and a boolean value that determines whether the function returns the cumulative or non-cumulative probability.
The first argument, the number of events, is the value you want to analyze. For example, if you’re interested in the probability of three customers visiting your store in a day, you would enter “3” as the first argument.
The second argument, the expected number of events, is the average number of events that you expect to occur in the given time period. For example, if you expect an average of five customers to visit your store in a day, you would enter “5” as the second argument.
The third argument, the boolean value, determines whether the function returns the cumulative or non-cumulative probability. If you enter “TRUE” as the third argument, the function will return the cumulative probability of the number of events occurring up to and including the value you entered as the first argument. If you enter “FALSE” as the third argument, the function will return the probability of exactly the number of events you entered as the first argument.
How to Use the POISSON.DIST Function in Power BI
Using the POISSON.DIST function in Power BI is easy. Here’s a step-by-step guide:
1. Open Power BI and create a new report or open an existing one.
2. Select the “Insert” tab from the ribbon menu and click on “Function”.
3. In the search bar, type “POISSON.DIST” and select it from the suggestions.
4. Enter the number of events you want to analyze as the first argument.
5. Enter the expected number of events as the second argument.
6. Enter “TRUE” or “FALSE” as the third argument, depending on whether you want the cumulative or non-cumulative probability.
7. Press “Enter” and the function will return the probability value.
Tips for Using the POISSON.DIST Function
Here are some tips for using the POISSON.DIST function effectively:
– Use it to analyze rare events: The POISSON.DIST function is best suited for analyzing rare events that occur randomly within a given time period. It may not be as effective for analyzing events that occur frequently or at regular intervals.
– Understand the expected number of events: The accuracy of the POISSON.DIST function depends on your understanding of the expected number of events. Make sure you have a good estimate of the average number of events that occur within the given time period.
– Use it in combination with other functions: The POISSON.DIST function is just one of the many statistical functions available in Power BI. Consider using it in combination with other functions to get a more complete picture of your data.
The POISSON.DIST function is a powerful statistical function in Power BI that helps you analyze the probability of rare events occurring within a given time period. By understanding how it works and how to use it effectively, you can gain valuable insights into your data and make better business decisions.