topic Re: Creating a Change Calculation based on SD's per month within a customised time frame. in Reporting Service & Alerting

Creating a Change Calculation based on SD's per month within a customised time frame.

lnn — Wed, 02 Aug 2023 03:15:51 GMT

I have a set of sales data that spans over a year. I want to be able to calculate the sum of change sales per month.

For example, say I selected a date range of 01 Feb 2023 - 30 Apr 2023 using my filter pane.

Feb sales were: 21, mar was: 22 and Apr was: 25 then the total change would be 4.

i.e. 22-21 = 1 and 25 - 22 = 3, 3+1 = 4

How do I create a query like this?

Re: Creating a Change Calculation based on SD's per month within a customised time frame.

cristianj23a — Wed, 02 Aug 2023 03:45:04 GMT

hi, try this code in script.

SalesData:
LOAD * INLINE [
Date, Sales
2023-01-01, 20
2023-02-01, 21
2023-03-01, 22
2023-04-01, 25
2023-05-01, 30
2023-06-01, 35
2023-07-01, 28
2023-08-01, 32
2023-09-01, 34
2023-10-01, 36
2023-11-01, 40
2023-12-01, 38
];

ChangeData:
LOAD
Date(MonthStart(Date)) AS MonthYear,
Sales - Previous(Sales) AS SalesChange
Resident
SalesData
Order By
Date;

Regarts.

Re: Creating a Change Calculation based on SD's per month within a customised time frame.

serives4 — Wed, 02 Aug 2023 11:11:10 GMT

Creating a change calculation based on standard deviations (SDs) per month within a customized time frame involves using statistical analysis to track the changes in a dataset over time. The goal is to determine how much the data deviates from the mean (average) and quantify these deviations using standard deviations. Here's a step-by-step guide to creating such a calculation:

Step 1: Data Collection: Gather the dataset that you want to analyze. This dataset should include data points collected at regular intervals (e.g., daily, weekly, or monthly) over your desired time frame.

https://community.qlik.com/t5/Reporting-Service/

https://ipayhourlycalculator.com/

Step 2: Calculate the Mean and Standard Deviation: Calculate the mean (average) and standard deviation of the dataset. The mean represents the central tendency of the data, while the standard deviation measures the variability or spread of the data points around the mean.