Basic Charts example

Basic Charts example

Problem Statement

Create an animation of different histograms by the nature of the distribution. Data is attached in attachement.

How to perform analysis

Step 1: Open Sigma Magic
  1. Click on the Sigma Magic button on the Excel toolbar.
  2. Click on the New button to create a new project.
Step 2: Add the analysis template
  1. Click on the Tool Wizard to add the analysis template.
  2. Click on Analytics and then Basic Charts.


Step 3: Specify analysis options
A new worksheet will be added to your workbook. Analysis Setup will be automatically opened, in the setup tab specify the survey results.



Click on Data to specify the data required for this analysis.



If you need to make changes to the charts, specify the optional settings in the Charts tab.

 Labels:

  • Add a title for the chart.
  • Label the X-axis and Y-axis appropriately.

Appearance:

  • Adjust colors, font sizes, or other visual elements as needed.
  • Enable/disable gridlines or background shading.


Click the Verify tab to ensure all the inputs are okay and shown in a green checkmark.


Step 4: Generate analysis result
Click OK and then click Compute Outputs to get the final results


Interpretation of Results

  • The analysis is performed on a single variable (X1), meaning the histogram represents the distribution of one dataset.
  • The dataset is extracted from "Table1," with the variable "X1" being analyzed.
  • The visualization is a histogram, which is used to understand the frequency distribution of numerical data.
  • The histogram shows a right-skewed (positively skewed) distribution, indicating that most of the values are concentrated on the lower end, while a few higher values extend the tail.
  • The title suggests that the dataset may follow a log-normal distribution, where data is normally distributed after applying a logarithmic transformation.
  • The histogram is grouped into bins of width 5, affecting how data is distributed visually. Smaller binwidths provide more detailed granularity, while larger binwidths smooth out variations.
  • The analysis does not include facet categorization (i.e., no grouping based on additional categorical variables) and does not have a legend.
  • The tool appears to allow state-based animation, potentially visualizing changes over time or multiple frames (frame 7 of 101 is displayed).
  • The output explicitly states that no detailed numerical analysis results are generated, meaning interpretation is based purely on the visualization.
  • The main outcome of this process is the successful generation of a histogram for exploratory data analysis (EDA),  helping to identify distribution characteristics, skewness, and outliers.


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