Unlock the potential of your data with SisTa-R as ease as never before
SisTa-R provides statistical analysis based on precise rules, thus helping your research data analysis to be more meaningful and correct so that your strategic recommendations can have an impact to policy decisions.
Call for partners and resources
Open for collaboration especially in upgrading and developing this app.
Unleash your growth potential with SisTa-R Version 1.0
for Correlation and Regression Analysis
From initial analysis, SisTa-R Version 1.0 is a user-friendly analytical tool designed to simplify and enhance the process of statistical analysis, particularly focusing on correlation (3 methods) and regression (17 methods) techniques on several data types such as continous, binary (0 or 1), count data (example: number of events), etc. Built on the powerful R programming language and implemented through the Shiny framework, SisTa-R empowers users—from students to researchers—to perform robust data analysis through an intuitive web-based interface.
Min-Max Normalization
Min-Max normalization scales data to a fixed range—usually [0, 1]. It preserves the relationships among the original values but brings them to a uniform scale.
Standardization (Z-score)
Standardization, or Z-score normalization, rescales data to have a mean of 0 and standard deviation of 1. This makes different variables comparable, especially when they are on different scales.
Logarithmic Transformation
The logarithmic transformation is used to reduce skewness and compress the range of data, especially when values span several orders of magnitude or contain exponential growth patterns. It is particularly helpful when data is right-skewed (long tail on the right) and Variance increases with the mean (heteroscedasticity).
Transforming your operations
with accurately data-driven insights
To improve model fit and meet statistical assumptions (such as normality and homoscedasticity), SisTa-R allows the users to apply a range of data transformations, including:
Preliminary Tests and Assumption Checks 🔬
SisTa-R has automated preliminary statistical tests and visual diagnostic tools to support assumption checking before proceeding with correlation or regression modelling such as:
Shapiro-Wilk Test and Kolmogorov-Smirnov test (for Normality),
[1] "✅ Residuals are normally distributed (p-value > 0.05)."
[1] "⚠️ Residuals are not normally distributed (p-value < 0.05). Consider using a different model or transforming the variables."
Breusch-Pagan Test for detecting Heteroscedasticity or Homoscedasticity (constant variance),
[1] "✅ No significant heteroscedasticity detected (p-value > 0.05)."
[1] "⚠️ heteroscedasticity is detected (p-value < 0.05)."
or other tests. Diagnostic Plots (QQ Plot. Residuals vs. Fitted Values Plot, Scale-Location Plot, Residual vs Leverage Plot, Histogram of Residuals, and Cook's Distance Plot, etc) also displayed to better understand the pattern of the data set. However, not all models have the same preliminary test methods. It is adjusted according to the selected model.
Correlation Analysis 📈
Correlation Analysis: Supports multiple methods including Pearson, Spearman, and Kendall to evaluate relationships between variables. The tool provides visualizations such as correlation matrices and scatterplots to aid interpretation.
Regression Analysis 📉
Breaking through the limits of reasonableness of regression analysis, Sista-R supports 17 regression models. Each model comes with detailed output summaries, diagnostic plots, and performance metrics (R², RMSE, AIC, etc.), making all forms of data is possible to be analysed without reducing the meaning contained in the data set.
Learn SisTa-R Version 1.0
Running the model & Downloading
Choosing variables and their types
decide your own variable and its type (numeric, factor, character)
Data transformation
Choose whether to use standardize, normalize, log-scaling or default (normal) to your data
Running the model
after all variables are set, just click once, and all statistical processing will run.
Downloading the plot figure
Downloading the plot result with changeable name of the X, Y, Z variables
Unfrequently asked questions
Please don't ask questions, especially outside of working hours because there is no overtime.
Our SisTa-R app specializes in data analysis and predictive modelling. We try to tailor our services to fit the unique needs of researcher across various sectors, helping them leverage data for informed decision-making.
Please do not emailing us at faozan2015@gmail.com, or calling +6289674974720. Our dedicated team is not available 24/7 to assist with any inquiries or issues.
However, If you have error or bugs, please tell us on working hours. We’re committed to maintenance and repair this app in order to delivering timely and effective data solutions to ensure your success career.
We believe that you don't care about our building code, you only care about what it is capable of. Although we write the cleanest and the most elegant code, as long as you found a bug, long processing loading time or even sometimes lagging, you will conclude that the app is useless. Perfection is a lie. In fact, the code itself helps solving your problems. Coding is problem solving, not just typing.
Similarly to above statement, We do not need your data anyway (-_-")....
See the video tutorial below
Leverage your workflow
with our analytics app
Sista-R version 1.0 was created autodidactically, looking at various apps on the internet, and sometimes combining existing ones with certain developments in them. The app building cost was very low, only requiring electricity, internet, a low-spec personal laptop computer (no SSD yet.... (>_<"), purchased in 2015 (more than a decade), not supporting for upgrade to windows 11, has replaced the battery for 3 times, charger for 2 times, and need 30 minutes to start booting into Windows (hahahaha ^_^). So, we had to be very patient in building this app.
Get in Touch with SisTa-R Version 1.0