Frequency Tables (Continuous Data)

Frequency Tables (Continuous Data)

Purpose

Produce summary tables and charts of data per attribute and per product if desired. This option is for continuous data e.g. Interval data on a scale from 1 to 100, or 1 to 10.

Data Format

  1. Profling.xlsx

Background

A frequency table lists a set of values and how often each one appears. Frequency is the number of times a specific data value occurs in a dataset. These tables help understand which data values are common and which are rare. These tables organize data and are an effective way to present the results to others.

For continuous data, the data must first be divided into classes before the frequencies can be counted. In this module, classes can be created of equal size – so that each class has the same frequency. Or they can be created of equal steps – so that the width of each class is the same.

Options

  1. Treat Sessions/Replicates separately: If the data has been gathered over different sessions, or there are different replicates, these can be analysed separately.
  2. Show Frequencies by Product: Yes/ No. If Yes, the data summaries are created by Product. If No, the data summaries are for the full data set.
  3. Show Percentages: Yes/ No. If Yes, a table of the frequencies as percentages is created. If No, this table of percentages is not created.
  4. Show Total: Yes/ No. If Yes, the table of frequencies with total is created. If no, this table of frequencies with total is not created. The total is the total frequency per class across all products.
  5. Sort Results from high to low: Yes/ No.  If Yes, the tables are sorted by class, with the class with the highest values on the scale as the first row of the table. If No, the tables are sorted by class, with the class with the lowest values on the scale as the first row.
  6. Type of Mean: Adjusted/ Arithmetic. The type of mean that should be computed. ‘Adjusted’ takes into account missing data or imbalance in design. The model attribute ~ product + assessor is used to calculate the adjusted mean.  ‘Arithmetic’ calculates the mean in the data and is recommend for balanced data.
  7. Definition of Frequency Classes: Equal in size / Equal in steps. If Equal in size is chosen the divided into classes so that each class has, as near as possible, the same frequency. Different class boundaries are selected for each attribute. If Equal in steps is chosen the interval is divided into equal sized steps to create the class boundaries.
  8. Number of Classes: The number of classes that should be created.
  9. Number of Decimals for Values: Required number of decimals for values given in the results.

Results and Interpretation

For each attribute the following tables are produced.

  1. Frequency. Tabulates the number of results in each of the classes as defined in the options. If Show Frequency by Product is chosen, then the counts are per product.The total N in each class and the mean of each class is given.
  2. Frequencies Plot. Shows a bar chart of the number of results in each class. If Show Frequency by Product is chosen, then the bar chart is per product. To hide / show a class in the chart, click on that class in the plot legend.
  3. Frequency percentages. If Show Percentages is set to Yes. Tabulates the number of results in each of the classes as a percentage of the total. Each column sums to 100%.  If Show Frequency by Product is chosen, then the percentages are per product.
  4. Frequency with Total. If Show Total is set to Yes. Tabulates the number of results in each of the classes as defined in the options. If Show Frequency by Product is chosen, then the counts are per product. An extra column, Total, gives the total number of results in each of the classes for all products.

Technical Information

  1. The SensoMineR package (Francois Husson, Sebastien Le, Marine Cadoret) is used to calculate the adjusted means.
  2.  The 2-way model attribute ~ product + assessor is used to calculate the adjusted mean.

References

  1. SensoMineR a package for sensory data analysis with R. http://sensominer.free.fr/
  2. Sheldon M. Ross (2017).  Introductory Statistics (Fourth Edition).  Elsevier Inc.

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