Learning aim B: Explore the statistical software tools and techniques used to analyse data in organisations B1 Statistical techniques The statistical requirements of operations when analysing data in organisations.
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Routine operations, including:
o
discrete data, continuous data, ungrouped data, grouped data
o
presentation of data: bar charts, pie charts, histograms
o
use of industry-standard software (e.g. spreadsheets, dashboards) to present
data in appropriate formats for audience and purpose
o
measures of central tendency: arithmetic mean, median, mode.
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Non-routine operations, including:
o
measures of dispersion: variance, standard deviation, range, interquartile and
inter-percentile ranges
o
use of spreadsheet and industry-standard software to calculate measures
of dispersion.
B2 Probability distributions The use of probability distributions process.
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Routine operations, including:
o
normal distribution: shape, symmetry, mean.
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Non-routine operations, including:
o
areas under the normal distribution curve relating to integer values of
standard deviation
o
use of industry-standard software, including spreadsheets and specialist
software, e.g. JMP and MATLAB
®
to determine if data represents a normal
distribution
o
comparison of the mean of two samples using software to carry out a t-test.
B3 Mathematical modelling of data to find a goodness of fit The requirements of mathematical modelling of data in the IT project.
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Linear relationship between independent and dependent variables, scatter
diagrams, approximate equation of line of regression
y =
mx +
c graphically.
•
Use of spreadsheet and industry-standard software to calculate an equation
of the line of regression and correlation coefficient.
•
Use of spreadsheet and industry-standard software to identify the most
appropriate type of regression line for a non-linear relationship.