Art of Stat: Explore Data 1.7.0

Bernhard Klingenberg ❘ Freeware ❘
iOS
de votos 13

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Modern statistical calculator for teachers and students of statistics.

The Art of Stat: Explore Data app offers a wide range of statistical methods tailored for exploring both categorical and quantitative data. Users can derive summary statistics, contingency tables, and correlation coefficients, as well as visualize data through bar charts, pie charts, histograms, boxplots (including side-by-side boxplots), dotplots, and interactive scatterplots that allow for dot coloration by a third variable. The application comes equipped with various example datasets for practice purposes, each including instructions on applying statistical analyses. Moreover, users have the flexibility to input custom data or import CSV files.

The app encompasses the following analytical methods:
<ul>
 <li>Analyzing One Categorical Variable</li>
 <li>Comparing Groups on a Categorical Variable</li>
 <li>Analyzing the Relationship Between Two Categorical Variables</li>
 <li>Analyzing One Quantitative Variable</li>
 <li>Comparing Groups on a Quantitative Variable</li>
 <li>Analyzing the Relationship Between Two Quantitative Variables (Linear Regression)</li>
</ul>

Key features of the application include:
<ul>
 <li>Frequency tables and bar and pie charts for probing single categorical variables.</li>
 <li>Contingency tables, conditional proportions, and side-by-side or stacked bar charts for exploring a categorical variable across multiple groups or assessing the correlation between two categorical variables.</li>
 <li>Calculation of mean, standard deviation, and the five-number summary in conjunction with histograms, boxplots, and dotplots for investigating quantitative variables.</li>
 <li>Side-by-side boxplots, stacked histograms, or density plots for group-wise comparison of quantitative variables.</li>
 <li>Interactive scatterplots featuring regression lines to scrutinize relationships between two quantitative variables. The app also provides correlation statistics, linear regression parameters and predictions, as well as plots of raw and studentized residuals.</li>
</ul>

In addition to the diverse functionalities offered, the application arrives with an array of example datasets readily available for exploration within the platform. Users can either directly access these datasets within the app to leverage its features or alternatively input their specific data or upload CSV files—compatible with most spreadsheet software—to select variables of interest. Furthermore, the application incorporates a fundamental spreadsheet tool titled Data Editor for creating and modifying datasets.

For added convenience, users can seamlessly copy and paste data from popular spreadsheet applications such as Google Sheets, Excel, or Apple’s Numbers app. The provided sample datasets serve as practical aids for familiarizing oneself with the application's capabilities.

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