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.
- 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
- Treat Sessions/Replicates separately: If the data has been gathered
over different sessions, or there are different replicates, these can be
analysed separately.
- 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.
- Show Percentages: Yes/ No. If Yes, a table of the frequencies as
percentages is created. If No, this table of percentages is not created.
- 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.
- 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.
- 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.
- 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.
- Number of Classes: The number of classes that should be created.
- 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.
- 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.
- 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.
- 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.
- 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.
- The SensoMineR package (Francois
Husson, Sebastien Le, Marine Cadoret) is used to calculate the adjusted means.
- The 2-way model attribute ~
product + assessor is used to calculate the adjusted mean.
References
- SensoMineR a package for sensory data
analysis with R. http://sensominer.free.fr/
- Sheldon M. Ross (2017). Introductory Statistics (Fourth Edition). Elsevier Inc.
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