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    Analyse-it Method Evaluation Edition

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    Building on the industry-standard spreadsheet, Analyse-it integrates into Microsoft Excel to provide you with a wide-range of statistics and charts for visualising, describing and testing hypotheses.

    Rated #1 in Microsoft Office MarketPlace
    For over 3-years now, Analyse-it has been consistently rated as the #1 statistical analysis add-in for Microsoft Excel at the Microsoft Office Marketplace.find out why over 15,000 customers rave about Analyse-it.

    Recognized  method validation software

    Supporting the latest CLSI and industry-recognised protocols, Analyse-it lets you meet CLIA, CAP, JCAHO & ICH-Q2A/B analytical method validation requirements to validate, verify & demonstrate analytical accuracy, precision, linearity, recovery, reference intervals, and diagnostic performance.

    • IVD companies can validate performance during development or when compiling final analytical performance claims for regulatory compliance.
    • Researchers can verify methods meet the manufacturer's analytical and diagnostic performance claims.
    • Laboratories can demonstrate performance of a new method to meet CLIA requirements, or demonstrate performance is back on track after a proficiency test failure.

    No other software provides such a range of easy-to-use tools for method evaluation at such an affordable price. That's why Analyse-it is now used by Abbott Diagnostics, Astra-Zeneca, Beckman Coulter, the FDA, Glaxo-Smith-Kline, Johnson & Johnson, Pfizer, and Roche, etc. It's easy to see why:

    • Easy-to-use data-entry templates for use by laboratory staff.
    • Accurate & reliable, avoiding tedious, error-prone hand calculations.
    • Print-ready reports, easily distributed to key laboratory staff by e-mail.
    • Runs as an add-in to Microsoft Excel, so there's virtually no learning curve.
    • A proven product, cited in hundreds of peer-reviewed papers over the last 10 years.
    • Includes all the statistics from the Analyse-it Standard edition

    Work within the familiar Excel environment

    Why learn how to use a complex statistics package? Analyse-it integrates into Excel ’97 to 2010 and provides a toolbar of dataset management and statistical tests so you can analyse data directly from your worksheet. Staying in the familiar Excel environment means there is virtually no learning curve!. You don't have to export your data to another package and you won't end up with your data locked into an in-accessible, proprietary, file format.

    Analyse-it integrates into Excel, providing a wide-range of statistics and charts for you to explore your data and test hypotheses -- all without leaving Excel.

    Explore, visualise and test sample distribution

    Analyse-it provides extensive descriptive statistics and insightful charts for exploring samples. Statistics include the mean, median & standard deviation, all with confidence intervals, plus many non-parametric measures such as quartiles & percentiles.

    box-whisker plots, mean-plots, percentile and standard deviation plots let you see how observations are distributed and spot outliers. A frequency histogram, with optional normal curve overlay, provides an alternative view of the sample distribution . Histogram bins can be determined automatically by Analyse-it or you can enter your preferred bins.

    Tests and charts include:

    • Summary statistics
    • Frequency histogram with configurable bins
    • Box-whisker plots, with near- & far- outliers
    • Dot-, Mean-, Percentile- & SD plots
    • 1-sample z-test
    • 1-sample t-test
    • Binomial test
    • Runs test

    Analyse-it provides many charts for exploring and visualising your data. Frequency histogram and dot- and box-whisker plot, with notch indicating median confidence interval, are shown.

    Verify pre-test assumptions of normality

    Tests and charts are included for verifying a sample is normally distributed -- a necessary step when using parametric statistics. Hypothesis tests are included so you can formally test normality, or you can use the normal quantile plot and frequency histogram (with normal overlay) to make a visual assessment.

    Tests and charts include:

    • Kolmogorov-Smirnov
    • Shapiro-Wilk (supporting upto 5,000 observations)
    • Anderson-Darling
    • Normal Quantile plot
    • Frequency histogram with normal overlay

    Find changes & differences between groups and samples

    Parametric procedures including the t-test and ANOVA, with post-hoc comparisons, are provided so you can test whether groups/samples change due to a factor or over time. For non-normal and categorical data non-parametric procedures are provided, including Mann-Whitney, Kruskal-Wallis, Fisher exact, and Chi-Square.

    Side-by-side dot-plots, box-whisker plots, & mean-plots, let you visually compare samples. Interaction plots, with connected means, let you easily see whether samples or groups differ or change.

    Tests and charts include:

    • Independent & paired t-test
    • Mann-Whitney & Wilcoxon Signed ranks
    • 1-way ANOVA, with LSD, Bonferroni, Tukey, Dunnet & Scheffe post-hoc comparisons
    • 1-way repeat-measures & 2-way ANOVA
    • Kruskal-Wallis & Friedman ANOVA
    • Sign & Median test
    • F- test
    • Fisher exact & Chi-Square
    • McNemar & Cochran tests
    • Side-by-side dot-plots, box-whisker plots, mean-plots & SD plots
    • Interaction plot (connected means)

    Analyse-it interaction plot connecting means of four samples to show the change over time. Error bars of the mean /- 2 SDs (standard deviations) are also shown to see the variation.

    Identify trends and relationships to make predictions

    For bivariate data, Analyse-it lets you explore potential trends with Pearson, Spearman, and Kendall correlation, and compare categorical ratings with Chi-square & Kappa.

    Where definite trends exist, the variables predicting the response can be identified with multiple linear regression and polynomial regression. Goodness of fit statistics and residual plots tell you how well the chosen variables predict the response. The equation to predict future observations is also shown.

    • Single & multiple linear regression
    • Polynomial regression
    • Scatter plot with fit, fit confidence and prediction bands
    • Raw and standardised residual plot
    • Histogram of residuals
    • Pearson, Spearman correlation
    • Kendall concordance
    • Kappa & Weighted Kappa
    • Bland-Altman agreement

    Analyse-it linear regression coefficients table and scatter plot showing the linear fit, confidence bands for the fit, and prediction bands.



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