# What can you do in BlueSky Statistics?

BlueSky Statistics offers over 100 frequently used exploratory analysis, data preparation, visualisation and basic modelling techniques, all accessible via an intuitive graphical user interface. The table below shows the range of tests and procedures that are available to you in BlueSky Statistics.

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Features |
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Exploratory Analysis |
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Analysis of missing values | ✓ | |

Summary Statistics of all Variables | ✓ | |

Summary Statistics by variable | ✓ | |

Summary Statistics by Group | ✓ | |

Numerical Statistical Analysis | ✓ | |

Visualization |
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Plot | ✓ | |

Histogram | ✓ | |

Boxplot | ✓ | |

Stem and Leaf Plot | ✓ | |

Plot of Means | ✓ | |

Strip Plot | ✓ | |

3D Scatterplot | ✓ | |

Bar graph | ✓ | |

Density plot | ✓ | |

Density Counts | ✓ | |

Scatter plot | ✓ | |

Others | ✓ | |

Scatter plot from Cars | ✓ | |

Boxplot (Lists outliers) | ✓ | |

Facets for scatter plot, box plot, bar graph, density plot | ✓ | |

Geographical Maps | ✓ | |

Heatmaps | ✓ | |

Data preparation |
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Remove missing values | ✓ | |

Recode | ✓ | |

Compute | ✓ | |

Sort | ✓ | |

Aggregate | ✓ | |

Bin | ✓ | |

Reload Dataset from File | ✓ | |

Refresh grid | ✓ | |

Standardize variables | ✓ | |

Subset | ✓ | |

Merge datasets | ✓ | |

Statistics |
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Hypothesis Tests | ✓ | |

Correlation Test | ✓ | |

Correlation Matrix | ✓ | |

Shapiro Wilk Normality Test | ✓ | |

Means | ✓ | |

Multi-variable One Sample T.test | ✓ | |

Independent Samples T.test | ✓ | |

Independent Samples T.test by factor | ✓ | |

Paired T-test | ✓ | |

One way Anova | ✓ | |

Multi-way ANOVA | ✓ | |

Variances | ✓ | |

Two variance F-test | ✓ | |

Bartlett’s Test | ✓ | |

Levene Test | ✓ | |

Non-Parametric Test | ✓ | |

2 Sample Wolcoxon Test | ✓ | |

Paired WilCoxon Test | ✓ | |

Friedman Test | ✓ | |

Kruskal Wallis test | ✓ | |

Tables and reporting |
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Contingency Tables | ✓ | |

2-way Crosstab | ✓ | |

Multi-way Crosstab | ✓ | |

Modeling and machine learning |
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Basic Modeling | ✓ | |

Linear Regression | ✓ | |

Logistic Regression | ✓ | |

Cluster Analysis | ✓ | |

Kmeans Clustering | ✓ | |

Hierarchical clustering | ✓ | |

Advanced Modeling | ✓ | |

Generalized linear models | ✓ | |

Multinomial Logit modeling | ✓ | |

Ordinal Regression | ✓ | |

Set Contrasts | ✓ | |

Display Contrasts | ✓ | |

Factor Analysis | ✓ | |

Factor Analysis | ✓ | |

Principal component Analysis | ✓ | |

Forecasting | ✓ | |

Plot time series | ✓ | |

Exponential smoothing | ✓ | |

Holt-winters Seasonal | ✓ | |

ARIMA models | ✓ | |

General capabilities |
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Richly formatted tabular output and output window that aggregates results from multiple analysis | ✓ | |

Export output to PDF, HTML | ✓ | |

Copy and paste tabular output to Excel | ✓ | |

Opening files in Different formats (Excel, CSV, SPSS, text, dat, SAS…) | ✓ | |

Converting from one file format to another | ✓ | |

The ability to split datasets | ✓ | |

Create new dialogs and output for any function in any R package using dialog editor. Install new dialogs. | ✓ | |

Display the R syntax associated with available analytical functions | ✓ | |

Run R syntax | ✓ | |

Batch Mode | ✓ |