technology.unstacked | R Documentation |
Case study from the technology market where 302 respondents rated how likely they were to recommend 13 tech brands. For a series of 9 attributes, the respondents indicated which brands they felt possessed the attribute.
This list contains two data.frame
elements:
Y
: A data.frame
that contains the recommendation values on a scale of 0 to 10.
This data.frame
has 13 columns, one for each brand (Apple
, Microsoft
, IBM
, Google
, Intel
, Hewlett-Packard
, Sony
, Dell
, Yahoo
, Nokia
, Samsung
, LG
, Panasonic
).
X
: A data.frame
that contains the respondents values for each attribute on each
brand. There are 117 columns, one of each of the 9 attributes by 13 brands. The nine attributes are (Fun
, Worth what you pay for
, Innovative
, Good customer service
, Stylish
, Easy to use
, High quality
, High performance
and Low prices
). The names of the columns are of the form 'attribute, brand'.
These data are available from the Q research software website. The address is: https://wiki.q-researchsoftware.com/images/3/35/Technology_2018.sav
More details of the analysis and stacking available in the 'How to do Driver Analysis: Ebook' available on the Displayr website. https://www.displayr.com
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