The pie chart below shows the frequency of U.S. Adults’ online purchasing habits in 2015, while the bar chart shows a further classification denoting online purchasing preferences. Summarise the data by selecting and reporting the main features and make comparisons where relevant.

The pie chart below shows the frequency of U.S. Adults’ online purchasing habits in 2015, while the bar chart shows a further classification denoting online purchasing preferences. Summarise the data by selecting and reporting the main features and make comparisons where relevant.
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The pie chart and the bar chart provide key information about the
adults
who bought goods online in 2015 and the classification of their shopping preferences. The units are measured in percentages.
Overall
, it is clear from the graph that more than one-third of
adults
shop
online less often.
In addition
, the majority of
adults
who
shop
less frequently online preferred to buy from stores,
whereas
the weekly online
shoppers
preferred to buy online.
According to
what is shown, a fifth of
adults
in the USA never tried to
shop
online,
while
more than a quarter of them
shop
online a few times a month.
Moreover
, the smallest proportion of them bought goods online weekly representing just 15%. In terms of shopping preferences, all online
shoppers
, monthly online
shoppers
, and less frequent online
shoppers
preferred to buy from shops with approximately 6%, 59%, and 81% respectively and just approximately 32%, 41%, and 19% to buy online respectively.
In contrast
, the weekly online
shoppers
preferred buying online with almost 62% and the remaining 38% liked to buy from stores.
Submitted by marim.almualim on

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Vocabulary: Replace the words adults, shop, shoppers with synonyms.
Vocabulary: The word "chart" was used 2 times.
Vocabulary: The word "approximately" was used 2 times.
Topic Vocabulary:
  • pie chart
  • bar chart
  • online purchasing habits
  • frequency
  • classification
  • summarise
  • main features
  • comparisons
  • demographics
  • consumer trends
  • e-commerce
  • data interpretation
  • purchasing categories
  • fiscal analysis
  • technological influence
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