The TFS Scrum and Agile templates come with a Velocity report. It includes the story points completed for each sprint and an average velocity. After 27 sprints and various changes to the team, earlier results are no longer relevant to calculating our current velocity.
The average for the entire life of the project is calculated as
=Avg(Fields!Story_Points.Value, "dsVelocity")
How do I calculate the rolling average for the last 6 sprints?
If you try to calculate the average velocity for your team over the last several sprints. It's impossible by now. It will include all sprints.
As a workaround, you may need to calculate this manually. You can also add a feature request in User Voice Site: https://visualstudio.uservoice.com/forums/330519-team-services
Related
Note: Not a data visualization expert
I'm working on a battle pass for a game that has Seasons running for set durations. I want to look at how users are progressing through the levels in the season.
What I'm seeking to answer is "How many users were at X level by day?"
I want this to be a time series with the days on one of the axis.
There is requirement where we have to calculate the throughput for the agile train teams. Is there any chart in JIRA using which we can calculate throughput for agile train teams.
Probably the closest thing to this is the control chart.
It will show you the rolling average of the mean time it takes for items to pass through your team's workflow.
This script might be really useful for you: http://www.littlebluemonkey.com/blog/automatically-import-jira-backlog-into-google-spreadsheet
It's a script that connects a Google Spreadsheet to Jira, bringing all the details related to your cards, so you can easily calculate throughput, lead time, flow efficiency, whatever the metrics you want.
Honestly the data quality in Jira round this can be a problem.
~ With a budget: Actionable Agile makes a great plugin that cleans it up. But there'd be a cost of course. https://www.55degrees.se/actionableagile
~ Without: Troy Megennis of Focused Objective is a writer and speaker who specializes in Coaching With Data. You could try his downloadable dashboard (requires Excel)
https://www.focusedobjective.com/w/support/
It also does Monte Carlo simulations
I'm new to SPSS. I have data of skin cancer diagnosis for the years 2004 - 2018. I want to compare the changes in distribution of new cases with regards to which body part and compare between the different years. I've managed to create a crosstab and grouped bar graph that shows the percentages but I would like to run a statistical analysis to see if the changes in distribution are significant over time. The groups I have are face, trunk, arm, leg or not specified, the number of cases for each year vary greatly which is why I'm looking to compare the ratios (percentages) between the different body sites. The only explanations I've found all refer to repeated observations of the same subject which is not the case here (a person is only included with their first diagnosis so can only appear in one of the years).
The analysis would be similar to comparing the percentages of an election between 3+ parties and how that distribution changes over the years but I haven't found any such tutorials. Please help!
The CTABLES or Custom Tables procedure, if you have access to it, will let you create a crosstabulation like you mention, and then will let you test both for any changes overall in the distribution of types, as well as comparing each pair of columns for each row.
More generally, problems like this would usually be handled as loglinear or logit models.
I´m working on a machine learning project where I try to predict, what clients will buy a specific product (buying the product is my target variable). I have plenty of features about the clients and enough historical data.
My issue is that my target variable is highly seasonal – most of the product is sold in December, other months have only little sales.
What do I have to do, to compensate this imbalance? Does the target variable need some adjustments? I need the model to have consistent performance across all months. Thanks
The simplest option would be to include month as a feature in some way. Some options for doing that:
One-hot-encode month. Pros: very simple, leads to rather sparse features set
Create a naive-bayes type feature encoding the prior probability of a sale in the given month. e.g. if 60% of sales are in December and uniformly 3.6% of sales in every other month, then this feature would have a value of 0.6 for every sale in December and 0.036 for sales in other months
For both of these methods you would want to ensure you have training data from a full 12 month period and separate evaluation set also from a full 12 month period.
we are using JIRA and Agile Board so we estimate the user stories with story points and JIRA takes care about burn down.
However we have also Tasks (not in user stories but single tasks) and bugs which can not be estimated in story points. After we solve those, we are estimating "work done" in terms of our story points and document them as "comments" in the tickets (bug or task)
Is there any plugin or tool, which can build a kind of burn up chart only for those (bugs and tasks) so that we can keep track.
At the end of a sprint, we do not have only burn down, but we also burn up and the effective real effort is the sum of those two.
The simplest thing to do would be to create a search that returned the issue types you were interested in and then export the data to Excel. You could then generate the burn up chart that you want.
I should note that you are not using story points in the usual Scrum fashion. Bugs and tasks are not usually counted in the team's velocity. They represent an overhead which reduces the team's ability to deliver stories (which are where business value is added).
Remember that velocity is not a measure of work done. It is instead a metric used to help with estimating what the team's capacity for delivering business value is in future sprints.