We are receiving a lot of questions about relevant analyses in the Analyse-it Method Validation edition to help in evaluating new diagnostic tests in the fight against COVID-19. Below are some quick links that will help, but contact us if you have questions - we are working as normal.
Also see our latest blog post: Sensitivity/Specificity and The Importance of Predictive Values for a COVID-19 test
There’s currently a lot of press attention surrounding the finger-prick antibody IgG/IgM strip test to detect if a person has had COVID-19. Here in the UK companies are buying them to test their staff, and some in the media are asking why the government hasn’t made millions of tests available to find out who has had the illness and could potentially get back to work.
We did a quick Google search, and there are many similar-looking test kits for sale. The performance claims on some were sketchy, with some using as few as 20 samples to determine their performance claim! However, we found a webpage for a COVID-19 IgG/IgM Rapid antibody test that used a total of 525 cases, with 397 positives, 128 negatives, clinically confirmed. We have no insight as to the reliability of the claims made in the product information. The purpose of this blog post is not to promote or denigrate any test but to illustrate how to look further than headline figures.
We ran the data through the Analyse-it Method Validation Edition version 5.51. Here's the workbook containing the analysis: COVID-19 IgM-IgG Rapid Test.xlsx
We used Analyse-it to determine the sensitivity/specificity and confirmed the performance claims on the website. The sensitivity is listed as 88.66% and the specificity 90.63%. Some websites also make an “accuracy” claim, usually a combination of (TP+TN)/Total, but that’s a useless statistic.
So, with reasonably impressive numbers around 90%, what’s the problem?
First, we need to look at the meaning of sensitivity and specificity:
These measures give the probability of a correct test result in subjects known to be with and without a condition, respectively. To understand how a test performs in the real world, we need to look at the predictive values. They tell us how useful the test would be when applied to a population. They indicate the probability of correctly identifying a subject's condition given the test result.
Here are the definitions of positive and negative predictive value:
Here’s where things get a little trickier. To calculate predictive values, the important numbers that we need to make decisions, we need to know the prevalence of COVID-19 in the population. And, at present, that’s an unknown.
We ran the numbers in Analyse-it using four scenarios for the prevalence of the illness of 1%, 5%, 10%, 20%.
The positive predictive value, that is, the probability that someone with a positive test result from this test has had COVID-19 illness is 8.7%, 33.2%, 51.2%, and 70.3%, respectively. Whilst the negative predictive values are 99.9%, 99.3%, 98.6%, 97.0%
To understand what’s going on here, we’ll use an example to show how the positive predictive value works.
Let’s assume you have a workforce of 100 staff to test (the population), and that the true unknown prevalence of COVID-19 illness in your workforce is only 5%. Therefore, 5 unknown staff have had the illness, and 95 have not. We apply the test to the population (all the staff) with the following results:
In total, 9 + 4 = 13 people tested positive as having had the illness. But, in truth, only 4 of 13 = 30% (as we see in Scenario 2 above) of those with a positive test have actually had the illness!
As can be seen in the example above, things aren’t as simple as they appear when you read a headline quoting a test with “90% accuracy”.
When applied to a population with a low prevalence of illness, the false positives soon overwhelm the true positives and make the test less useful. If applied to populations with a higher prevalence of the illness, such as workers who have had symptoms and self-isolated, the usefulness of the positive test result increases (see, for example, Scenario 4 in the table above).
This paper presents just one example of a single
test, and others with higher sensitivity/specificity will perform better. It highlights the importance of predictive values in decision making, and in evaluating whether a particular test is really that helpful.
We’ve been busy over the last few months adding
various new features and improvements to Analyse-it.
There are always many
changes behind the scenes, which aren’t really news-worthy, but seek to make
Analyse-it compatible with the latest changes to Microsoft Excel and Windows. Microsoft
have recently embraced a more aggressive continuous-release deployment model
with Office and Excel, and these releases have caused quite a few headaches for
developers, notably with the .
Our focus at Analyse-it has always been on the development and improvement of our software. While we provide extensive help, tutorials, and technical support for Analyse-it, one area we do not cover is training and consultancy. As many of you will know we are based in England in the United Kingdom, and providing training and consultancy is often done better locally, in-person.
Instead we partner with experts who can provide training and consultancy in various disciplines, in local language, and geographically near (or at least nearer) to our customers. You can always find a list of current consultant and training partners at
It’s been a long-requested feature, and today we’re happy to announce that Analyse-it version 5.10 now includes the ability to save the dataset filter with an analysis and re-apply it on recalculation.
Analyse-it always allowed you to use Excel auto-filters to quickly limit analysis to just a subset of the data, but until now that filter wasn’t saved. Each time you recalculated the analysis it was based on the currently active filter rather than the filter in-effect when you created the analysis.
Update 19-Sep-2019: Unfortunately this continues to be an issue for some users and unfortunately there is currently no solution from Microsoft except to suggest the use of compatibility mode as detailed below. We have requested this be fixed, so please up-vote it at
Update 27-Jun-2018: Although we have a fix for this issue on an internal build, it appears that Microsoft Office version 1807 (which is currently only available on the Office Insider track) fixes this issue. The missing user-interface problem was caused by a bug in Microsoft Office 1805/1806 updates. We will release our fix shortly, but the 1807 version update will also become available to everyone over the next month or so. If you want to get it immediately see .
Today marks the 20th birthday of Analyse-it.
It was December 1997 when we shipped the first disks containing Analyse-it to paying customers. In some ways it seems just like yesterday, but in other respects software development and Analyse-it has come so far in those 20-years.
As many of you know Analyse-it wasn’t our first foray into developing statistical software. My co-founder in Analyse-it, Simon Huntington, had previously developed . Astute was the first statistical add-in for Microsoft Excel, initially released in 1992 for Excel 4.0, and released a few months before Microsoft’s Data Analysis Toolpak which appeared in Excel 5.0.
Prediction intervals on Deming regression are a major new feature in the Analyse-it Method Validation Edition version 4.90, just released.
A prediction interval is an interval that has a given probability of including a future observation(s). They are very useful in method validation for testing the commutability of reference materials or processed samples with patient samples. Two CLSI protocols, and both use prediction intervals.
Often we collect a sample of data not to make statements about that particular sample but to generalize our statements to say something about the population. Estimation is the process of making inferences about an unknown population parameter from a random sample drawn from the population of interest. An estimator is a method for arriving at an estimate of the value of an unknown parameter. Often there are many competing estimators for the population parameter that differ based on the underlying statistical theory.
As we mentioned last week in the , in this release we took the opportunity to revamp the documentation.
The revamp involved rewriting many topics to make the content clearer, adding new task-oriented topics, including refresher topics on common statistical concepts, and improving the indexing and links between topics so you can more easily navigate the help system.
The new task-oriented topics give you step-by-step instructions on completing common tasks. For example you will now find topics on how to , , , and even simple tasks like . We have also fully documented the supported dataset layouts for each type of analysis so you can see how to arrange your data for Analyse-it. The links in each topic help you more easily find related topics, for example links to topics on how to interpret the statistics, links to explain the pros and cons of the available statistical tests, links to topics for common tasks, and a link showing you how to arrange the dataset.
Last week we released version 4.80 of Analyse-it.
The new release includes multi-way , , and in the Standard edition, and since every licence includes the Standard edition, these features are available to all users. We also took the opportunity to revamp the and develop a . We’ll go into more details on the improvements in the next few weeks.
If you have you can download and install the update now, see . If maintenance on your license has expired you can renew it to get this update and forthcoming updates, see .
Today we released version 4.60 of the Analyse-it Method Validation edition.
The new release now includes 3 nested-factor precision analysis, which extends Analyse-it’s support for CLSI EP05-A3 multi-laboratory precision studies.
We are delighted to announce the addition of the Analyse-it Quality Control and Improvement Edition to the range of Analyse-it products.
The new edition includes the most impressive statistical process control (SPC) charts available in any Excel statistical software package, including Shewhart, Levey-Jennings, CUSUM, and EWMA charts. Process capability statistics and plots help you ensure a process is able to meet specifications. And Pareto plots help you identify the quality-related problems that need the most attention and let you monitor efforts to reduce them.
Microsoft officially released a couple of days ago, and Analyse-it version 4.20 now adds support for Excel 2016.
Over the next few weeks we will tweak the Analyse-it user interface so it matches the new Office 2016 user interface styles. Line styles on the plots in Excel 2016 now also appear a lot thicker, due to anti-aliasing (smoothing), so we will decide whether to address that in a future update – let us know what you think.
A critical feature of any analytical and statistical software is accuracy. You are making decisions based on the statistics obtained and you need to know you can rely on them.
We have documented our previously, but another good benchmark to test statistical software against is the NIST StRD. The Statistical Engineering and Mathematical and Computational Sciences Divisions of NIST’s Information Technology Laboratory developed datasets with certified values for a variety of statistical methods against which statistical software packages can be benchmarked. The certified values are computed using ultra-high precision floating point arithmetic and are accurate to 15 significant digits.
Today we released version 4.0 of the Analyse-it Method Validation edition. This is a major new release with many new features and improvements.
The latest release of the Analyse-it Method Validation edition now supports 10 of the latest CLSI evaluation protocol (EP) guidelines. guidelines are world-renowned and are recognized by the College of American Pathologists (CAP), The Joint Commission, and the US Food and Drug Administration (FDA).
The recent of passing of Professor Rick Jones (see ) caused me to reflect on the past.
I was very fortunate to earn a work placement with Dr Rick Jones at The University of Leeds in the summer of 1990. Rick was enthusiastic about the role of IT in medicine, and after securing funding for a full-time position he employed me as a computer programmer. Early projects included software for automating the monitoring of various blood marker tests and software to diagnose Down’s syndrome. At the time many hospitals had in-house solutions for diagnosing Down’s syndrome, and although the project took many years and the help of many other people to complete, it eventually gained widespread adoption.
Today we released version 3.80 of the Analyse-it Standard edition.
The new release includes Principal Component Analysis (PCA), an extension to the multivariate analysis already available in Analyse-it. It also includes probably the most advanced implementation of biplots available in any commercial package.
New features include:
The tutorial walks you through a guided example looking at how to use correlation and principal component analysis to discover the underlying relationships in data about New York Neighbourhoods. It demonstrates the amazing new features and helps you understand how to use them. You can either follow the tutorial yourself, at your own pace, or .
If you you will no doubt already know about the recent improvements in the Analyse-it Method Validation edition and the release of our first video tutorial. If not, now is a good time to since we post short announcements and feature previews on Facebook, and use the blog only for news about major releases.
The latest changes and improvements to the Analyse-it Method Validation edition include:
Today we released version 3.70 of Analyse-it.
The new version includes many new features which some of you may have read about on our page over the last few weeks:
New features include:
If you have you will be notified an update is available when you next start Analyse-it, or you can download and install the update now, see . If maintenance on your licence has expired now is a good time to renew it to get this update and forthcoming updates, see .
Probably the greatest concern when using statistical software is reliability. Is the software producing accurate, numerically correct results that have been validated?
It’s a very important question. Many of you work in FDA and regulated environments where the penalties for mistakes are very high. And those of you outside such environments are still making important business and research decisions using Analyse-it. It’s therefore imperative that the software you depend upon is developed to a professional standard, thoroughly tested and validated.
We have just released version 3.60 of the Analyse-it Standard edition. It now includes repeat-measures ANOVA and Friedman tests in the Compare Pairs analysis.
If you have active maintenance, Analyse-it will notify you an update is available in the next few days, or you can download it immediately at:
If you do not have active maintenance, now is a great time to extend maintenance to get this latest update and all updates for the next 1- or 3-years, see:
Today we released the Analyse-it Method Validation edition version 3.5. The software is feature complete, validated, and includes documentation. It supports Excel 2007, Excel 2010 (32- and 64-bit) and Excel 2013 (32- and 64-bit).
We took this opportunity to rename the product from the Analyse-it Method Evaluation edition to the Method Validation edition. The product is the same, but the new name better reflects the intended purpose of the product.
Today we released the first public beta test version of the Analyse-it Method Evaluation edition, version 3.5. The software is feature complete and is validated – it is now only missing documentation.
We invite everyone to download the beta and try the new version of the software before it is finally released in September. You will need Excel 2007, 2010, or 2013 (32-bit and 64-bit versions are supported) and it can be installed and used alongside older versions of Analyse-it so it won't interrupt your day-to-day work.
Today we released the 3rd alpha release of the Analyse-it Method Evaluation Edition 3.5. Alpha releases are versions of the software that are still in active development, but are released to small group of customers so we can identify and fix any problems before the public beta release.
This release now completes the package with method comparison, which includes Deming regression, Passing-Bablok regression, and Bland-Altman difference plots. Linearity, precision analysis, diagnostic performance (ROC analysis and binary test performance) and reference intervals were already included in earlier alpha releases.
Today we released the 2nd alpha of the Analyse-it Method Evaluation Edition 3.5.
Alpha releases are pre-release versions of the software that are still in active development. We release them to a small group of customers so we can get feedback and quickly identify and fix any problems before the public beta release. If you want to take part in the test phase reply or comment on to this post or . You can use pre-release versions of Analyse-it alongside your
existing version of Analyse-it, so it won't disrupt your work. And, if you help during in the test phases you will get a discount on the upgrade (a free upgrade for those who contribute the most) when the product is released later this year.
We are now starting to release test previews of a major update to the Analyse-it Method Evaluation edition. The new release will include many new features (we'll reveal more in the coming weeks) and will support 32- and 64-bit versions of Excel 2007, 2010, and 2013.
During the initial test phases we release development versions of the application to a small group of customers to ensure it installs and runs as expected on a wide range of PCs and configurations. The official beta test phase stage then follows where more customers are invited to download and use the software, while we iron-out the final few bugs before the official release. The official release is planned for summer 2013.
What is a sample quantile or percentile? Take the 0.25 quantile (also known as the 25th percentile, or 1st quartile) -- it defines the value (let’s call it x) for a random variable, such that the probability that a random observation of the variable is less than x is 0.25 (25% chance).
A simple question, with a simple definition? The problem is calculating quantiles. The formulas are simple enough, but a take a quick look on Wikipedia and you’ll see there are at least 9 alternative methods . Consequently, statistical packages use different formulas to calculate quantiles. And we're sometimes asked why the quantiles calculated by Analyse-it sometimes don’t agree with Excel, SAS, or R.
Yesterday we improved the help in the and added a statistical reference guide. The guide tells you about the statistical procedures in Analyse-it, with help on using and understanding the plots and statistics. It’s a work in progress, and we intend to improve it further with your comments and feedback, but it’s important to understand the role of the guide.
Firstly, the guide is not intended to be a statistics textbook. While it covers key concepts in statistical analysis, it is no substitute for learning statistics from a good teacher or textbook.
Leeds, England (PRWEB) October 03, 2012 -- Analyse-it Software, Ltd. today announced a major new release of their popular , Analyse-it®. With support for Excel 2007, 2010 and the forthcoming Excel 2013, Analyse-it transforms Microsoft Excel into a cost-effective powerful statistical analysis and data visualization package. Statistics and plots are included for exploring and describing data, estimating parameters, testing hypotheses, uncovering relationships and fitting models.
Today we pushed the release candidate of the Analyse-it Standard Edition v3.0 for Microsoft Excel 2007 & 2010, our statistical analysis software for Microsoft Excel.
The release candidate is feature complete and is intended to be the final, almost public release of the software.
The software is now validated against our library of thousands of tests to ensure the statistics and plots are accurate and correct. You can now use the software in your day to day work and, like previous versions, it can be used alongside your current version of Analyse-it until you become more comfortable with it.
We’re pleased to release the final beta of the Analyse-it Standard Edition, v3.0. The beta is now publicly open to anyone as we iron out any final issues and conduct final testing before release.
To download the beta, please visit:
Screenshot: Analyse-it fit model analysis includes an influence plot to identify points with a substantial effect on the fitted model.
Today we released the first public beta of
Analyse-it Standard Edition, v3.0.
Maybe we're biased, but it is an amazing product! It's been a heck of a lot of work, but the range
of statistical tests and plots in Analyse-it v3 rival what the expensive, established statistical packages provide. In fact, in many cases we’ve surpassed what
they offer. And the statistical plots go beyond what's available in any
other Excel add-in.
If you follow us on you will have seen that we released a new version of the Analyse-it Standard Edition, v3.0, to testing this week.
During the initial test phases we release development versions of the application to a small group of customers to ensure it installs and runs as expected on a wide range of PCs and configurations. The official beta test phase stage then follows where more customers are invited to download and use the software, while we iron-out the final few bugs before the official release. The official release is planned for early 2012.
It's been a few months since we released Analyse-it 2.22, which added compatibility with, what was then, the Excel 2010 release candidate. Now it seems many are upgrading from Excel 2003 and are contacting us to ask whether Analyse-it is compatible. It is!
Interestingly, starting with Office 2010, Microsoft is providing 32- and 64-bit versions of Microsoft Excel. Until now Excel has been a 32-bit application only (going back to Excel 5 which was a 16-bit application). natively supports the 64-bit microprocessors becoming more common in desktop PCs and allows you to work with truly enormous quantities of data.
Yesterday Microsoft launched . It’s the next version of Windows, following on from Windows Vista, Windows XP, and Windows 2000.
As a software vendor we had early access to Windows 7 and have been using it daily for approximately 6-8 months. Our impressions are Windows 7 is very reliable, stable, much faster than Vista, and is an upgrade we wouldn’t hesitate to recommend.
Today we released the latest update to Analyse-it, version 2.20, which includes some minor fixes and major improvements. The major improvements affect users of Excel 2007, though we recommend all users download this update for the minor fixes included.
Late last week Microsoft started to release Microsoft Office 2007 Service Pack 2, and made it publicly available on Tuesday this week. Service Pack 2 includes many improvements, including some worthy performance improvements for users of Microsoft Outlook.
The British government recently announced a 2.5% reduction in VAT (sales tax) on goods purchased from the United Kingdom (see ). UK VAT was previously 17.5%, but from the 1st December 2008 until the end of 2009 it has been reduced to 15%.
Like many businesses, last Monday, we implemented the change.
Customers in the United Kingdom who aren’t VAT exempt, and those of you in Europe who are not VAT registered and must pay VAT, will now pay only 15% VAT.
In clearly titling this blog post, we’ve probably already revealed the answer, but... Can you spot the difference between the two rows of values in the Excel spreadsheet shown below?
Sorry, it’s a trick question, because (visually) there is no difference. The difference is how the values are stored by Microsoft Excel. The value 57 in the cell on second row is actually stored as a text string, not a number.
Today we’re delighted to publish the second case study into the use of Analyse-it.
The case study features a national clinical laboratory in the USA that offers more than 2,000 tests and combinations to major commercial and government laboratories. They use Analyse-it to determine analytical performance of automated immunoassays for some of the industry’s leading in-vitro diagnostic device makers -- including Abbott Diagnostics, Bayer Diagnostics, Beckman Coulter and Roche Diagnostics.
In a previous post, , we explained the tests provided in Analyse-it to determine if a sample has normal distribution. In that post, we mentioned that although hypothesis tests are useful you should not solely rely on them. You should always look at the histogram and, maybe more importantly, the normal plot.
The beauty of the normal plot is that it is designed specifically for judging normality. The plot is very easy to interpret and lets you see where the sample deviates from normality.
A customer contacted us last week to ask how to refer to cells on an Analyse-it report worksheet, from a formula on another worksheet. The customer often used Analyse-it's refresh feature, to repeat the statistical analysis and update the statistics, and direct references to cells on the report were being lost on refresh.
As an example, suppose you have used Analyse-it linear regression to calculate the linear relationship between installation cost and the number of employees required, distance to the site, and the cost of machine being installed. Analyse-it would calculate the effect of each variable on the final cost, technically known as regression coefficients, which you can then use to predict installation costs for jobs in future.
Today we’re delighted to publish the first case study into the use of Analyse-it.
Marco Balerna Ph.D., a Clinical Chemist at the in Switzerland, used Analyse-it when replacing the clinical chemistry and immunological analysers in EOC’s laboratories.
Since the EOC provides clinical chemistry services to five large hospitals and three small clinics in the region, it was essential the transition to the new analysers went smoothly. Marco used Analyse-it to ensure the analyser’s performance met the manufacturer’s claims, to ensure the reporting of patient results was not affected, and to comply with the regulations of the EOC’s accreditation.
Last Friday we released the latest update to Analyse-it, version 2.12 -- a minor update, providing fixes to minor issues recently reported by customers. The update is available free.
If you're using , and not experiencing any of the issues fixed (see the ), then you can skip the the update if you wish. But if you're using an earlier version of Analyse-it, version 2.10 or earlier, we recommend you get the update.
Although the charts in Analyse-it are large so they’re easy to read when printed, sometimes you need to print a chart to fill the full page. You can do so easily, without resizing the chart, in just a few steps:
Chart size is only limited by the page size your printer supports.
We’re pleased to announce that from today we can accept payment in EUROs. You can now see prices for Analyse-it in EUROs, as well as British Pounds sterling, and US dollars (for customers in the USA & Canada).
The EURO is now the primary currency in Europe and many of our customers have asked us to accept EUROs. We can accept payment in EUROs by VISA, MasterCard or AMEX credit card, or by cheque or wire-transfer.
Identifying what was analysed, when, and by who, is the first step in understanding any Analyse-it report. The top rows of each Analyse-it report provide you with this information. The statistical test used, dataset and variables analysed, user who analysed, and the date and time last analysed, are included (see below). When you print the report the header is repeated at the top of printed page.
In May this year, we surveyed users of the Analyse-it Method Evaluation edition to gain insight into how we can improve Analyse-it in future. Thank you to all those who responded.
In the responses, one issue became clear: the unfiled reports feature causes confusion.
When you run an analysis, Analyse-it creates a new worksheet containing the statistics and charts for that analysis (what we call a report). Analyse-it places the report in a temporary workbook called . From there you can then decide what you want to do with the analysis: keep it, print it, e-mail it, or discard it. If you want to keep it you click the (see below), and Analyse-it moves the report into the same workbook as your dataset.
The most used distribution in statistical analysis is the normal distribution. Sometimes called the Gaussian distribution, after , the normal distribution is the basis of much parametric statistical analysis.
Parametric statistical tests often assume the sample under test is from a population with normal distribution. By making this assumption about the data, parametric tests are more powerful than their equivalent non-parametric counterparts and can detect differences with smaller sample sizes, or detect smaller differences with the same sample size.
For new and occasional Analyse-it users, datasets can sometimes seem confusing. Today we’ll explain why we devised the 'dataset' concept, a concept now copied by some other Excel add-ins.
We introduced the dataset concept so Analyse-it could automatically pick-up the data and variables from your Excel worksheet. As we found with , the Analysis Toolpak, and other Excel add-ins, forcing you to select cells containing the data to be analysed can be problematic:
A few readers have e-mailed to ask for more information about the book by David J. Sheskin we alluded to in the comment reply re: the , last week.
The book is the Handbook of Parametric & Non-parametric Statistical procedures, by David J. Sheskin, ISBN: 1584888148.
We have the third edition of the book which runs to over 1,200 pages -- a phenomenal piece of work for a single (obviously very dedicated) author. While it’s not a book you would sit down and read cover-to-cover, it is a very readable reference guide, covering all the parametric and non-parametric statistical procedures included in Analyse-it.
Many Analyse-it users readily admit their statistics knowledge is a little rusty, usually because it’s 10 years or more since their last statistics course. Should I use the t-test, Mann-Whitney, or Wilcoxon test? The names of the tests aren’t exactly helpful, nor do they give you any clue of the assumptions that must be met to use the test.
That’s why we devised the .
It’s a simple interactive wizard that asks what you want to do, what data you’ve observed, checks which pre-test assumptions can be met, then tells you the best statistical test to use. Using the advisor you can be confident you’re using the correct statistical test -- or even use it to check if your statistics knowledge really is as rusty as you think!
Depending on where you’re located, the way we spell “Analyse-it” may intrigue you. We chose the name in 1997 as it sounded active, a direction to analyse it! – similar to many product names of the time.
The name has served us well and hints as to what our business and product offers.
At the time we didn’t think such a simple name would cause so many headaches. Before you wonder, Analyse-it doesn’t mean anything offensive in other languages, but it can be spelt different ways:
Most of you know where to find the help and examples provided with Analyse-it, but if not, today we’d like to explain what’s available. If you're stuck we're always happy to help, and usually respond within a few hours, but it's always faster for you to check if the help answers your question first.
If you’re new to Analyse-it, or want a quick refresher, the best place to start is the Getting Started tutorial. It’s completely automated, no typing is required, so all you have to do is sit back and watch. In just 10 minutes it will demonstrate how to setup a dataset, how to filter the dataset, how to run a statistical test, and how to edit, refresh, and print the reports.
One of the primary reasons we launched the blog is to let you know what we’re currently working on, and give you to opportunity to feedback and influence the development.
At the moment we're spending most of our time developing version 3.0 of the Analyse-it Standard edition. The improvements are based on what you've asked us to include, and through insights gleaned from recent customer surveys. Improvements and new features will include:
Last Friday we released the latest update to Analyse-it, version 2.11. It’s a minor update providing minor fixes to issues recently reported by customers.
The update is available free to everyone, including users still using Analyse-it version 1.
In fact if you’re still using Analyse-it version 1 you should get the update right away. You’ll be impressed with the improvements to both the application and help, and if you’re using Excel 2007 you’ll love the slick Analyse-it RibbonBar .
Thanks for stopping-by to read the inaugural post to the Analyse-it blog.
We’ve launched the to keep you up-to-date on what’s new at Analyse-it, what we’re working on, and to notify you when updates and new products are released. We’ll also blog about using Analyse-it, statistical analysis, and interpretation.
The best part about the blog is it’s a conversation -- a conversation between you, our visitors and customers, and us. After reading a post you can add your thoughts, suggestions, and comments. We’ll reply when necessary or other visitors can post their opinions to ignite the debate. Click the links at the end of each post to read comments or add your own.