Choose your Application
All applications are developed with R and Shiny.
Some applications will ask you to copy and paste data from excel, others to upload files in csv format.
In your csv file, data must be separated by commas and the decimals indicated with dot. Check it. For problems use the Forum
Your data are uploaded and analyzed. After analysis they are discarded. During the analysis and after the analysis they are not displayed, they are not stored and they can not be used by any other user or administrator
Legal Disclaimer:
These applications for statistical analysis of data are strictly research tools. Our team has made every attempt to ensure the accuracy and reliability of the information provided by all the applications. However, the information is provided "as is" without warranty of any kind. Neither University of Pavia nor the investigators accept any responsibility or liability for the accuracy, content, completeness, legality, or reliability of the information provided by these software.No warranties, promises and/or representations of any kind, expressed or implied, are given as to the nature, standard, accuracy or otherwise of the information provided by these software nor to the suitability or otherwise of the information to your particular circumstances.
A chisquared test, also written as χ2 test, is any statistical hypothesis test where the sampling distribution of the test statistic is a chisquared distribution when the null hypothesis is true. The chisquared test is used to determine whether there is a significant difference between the expected frequencies and the observed frequencies in one or more categories
Nonparametric statistics is the branch of statistics that is not based solely on parametrized families of probability distributions. Nonparametric statistics is based on either being distributionfree or having a specified distribution but with the distribution's parameters unspecified. Nonparametric statistics includes both descriptive statistics and statistical inference.

MannWhitney Utest

Wilcoxon signedrank test

KruskalWallis test

Friedman test
Nonparametric statistics is the branch of statistics that is not based solely on parametrized families of probability distributions. Nonparametric statistics is based on either being distributionfree or having a specified distribution but with the distribution's parameters unspecified. Nonparametric statistics includes both descriptive statistics and statistical inference.

Check Normality and Homoscedasticity

Student's ttest

Paired Student's ttest

One way ANOVA
Analysis of variance (ANOVA) is a collection of statistical models and their associated estimation procedures (such as the "variation" among and between groups) used to analyze the differences among group means in a sample. In its simplest form, ANOVA provides a statistical test of whether the population means of several groups are equal, and therefore generalizes the ttest to more than two groups. ANOVA is useful for comparing (testing) three or more group means for statistical significance.

Check Normality

Check Homoscedasticity

Test Hypotheses

Post hoc Tests
The general purpose of multiple regression (the term was first used by Pearson, 1908) is to learn more about the relationship between several independent or predictor variables and a dependent or criterion variable.

Multiple Linear Regression

Multiple Logistic regression
Principal component analysis (PCA) is a statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables called principal components. PCA is mostly used as a tool in exploratory data analysis and for making predictive models
Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some sense) to each other than to those in other groups (clusters). It is a main task of exploratory data mining, and a common technique for statistical data analysis

Data Preprocessing

PCA

Heat Map
Survival analysis is a branch of statistics for analyzing the expected duration of time until one or more events happen, such as death in biological organisms and failure in mechanical systems.
Metaanalysis is a quantitative, formal, epidemiological study design used to systematically assess previous research studies to derive conclusions about that body of research. Outcomes from a metaanalysis may include a more precise estimate of the effect of treatment or risk factor for disease, or other outcomes, than any individual study contributing to the pooled analysis

Inter rater reliability

Model Options

Pubblication BIAS

Effect SIZE Calculation
Structural equation modeling (SEM) is a form of causal modeling that includes a diverse set of mathematical models, computer algorithms, and statistical methods that fit networks of constructs to data.
A scatter plot can be used either when one continuous variable that is under the control of the experimenter and the other depends on it or when both continuous variables are independent.
Create your Personalized Scatter Plot
The tool allows a graphical analysis of the data producing different types of highlevel graphs

BoxPlots

Density Plots

Line Plots

Bar Plots

Kaplan Meier Plots

Histogram Plots

Scatter Plots

Quantile Regressions
Create your Personalized Plot

Gene Annotation

Prioritization

LiftOver

VCF File analysis

Pathway Enrichment

Variant Effect Prediction

Others
Statistical power is a fundamental consideration when designing research experiments. It goes handinhand with sample size. The formulas that our calculators use come from clinical trials, epidemiology, pharmacology, earth sciences, psychology, survey sampling ... basically every scientific discipline.
Text analysis involves information retrieval, lexical analysis to study word frequency distributions, pattern recognition, tagging/annotation, information extraction, data mining techniques including link and association analysis, visualization, and predictive analytics.
Machine learning (ML) is a category of algorithm that allows software applications to become more accurate in predicting outcomes without being explicitly programmed. The basic premise of machine learning is to build algorithms that can receive input data and use statistical analysis to predict an output while updating outputs as new data becomes available.
This shiny app can help the users to compare different smoothing models in forecasting, namely simple exponential smoothing, linear exponential smoothing and HoltWinter method. Users can set the confidence interval and forecasting horizon by themselves. Also, users can choose to put in their own model parameters and see the difference between same model with different sets of parameters. The demo data set in app is “airpass” data set inserted in R package “fma”, you can also choose to upload your own data set.