VCE Data Analytics U4O1 Word Scramble: Audience and developing infographics and dashboards to Data quality and testing visualisations (Modules 63–83)
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Word scramble
Unscramble the letters and write each key term on the line.
1
OGINPITANA
Dividing content across separate pages or screens in a planned order, so each holds a manageable amount, such as one message per page.
2
ERFERSH QMREURNTSEIE
Statements of how often, how and by whom the data behind a dynamic visualisation is updated, e.g. a daily automatic refresh from the data source.
3
IULVSA AHECRIYHR
Using size, colour, weight and position so the viewer's eye goes to the most important element first, then follows a clear reading order to the rest.
4
RTIACYL FO EAGSMSE
When a viewer can state a visualisation's main point in seconds, thanks to a title that states the finding, no clutter, one message per visual and readable labels.
5
FI AMNE != ""
An existence check tests that the user actually entered something, so the input is not an empty string. len(name) > 0 does the same job. Loop and re-ask until it passes.
6
DIGIITS()
A type check method: returns True if a string holds only digits, so text can be rejected where a number is needed. The alternative is to put int(value) inside try/except.
7
FI 0 <= AKRM <= 001:
A range check tests that a number lies between a minimum and maximum. This chained comparison is True only when mark is from 0 to 100 inclusive, so the boundary values 0 and 100 are accepted.
8
FAICRNEIVTIO
Checking that data was entered or copied exactly as it appears in the source, such as by double entry or comparing it with the original. It checks accuracy, not reasonableness.
9
RGNDFAERIPOO
Carefully reading text, labels and figures to find and fix spelling, wording and number errors before you publish your work.
Answer Key
VCE Data Analytics U4O1 · Modules 63–83
1OGINPITANA → pagination — Dividing content across separate pages or screens in a planned order, so each holds a manageable amount, such as one message per page.
2ERFERSH QMREURNTSEIE → refresh requirements — Statements of how often, how and by whom the data behind a dynamic visualisation is updated, e.g. a daily automatic refresh from the data source.
3IULVSA AHECRIYHR → visual hierarchy — Using size, colour, weight and position so the viewer's eye goes to the most important element first, then follows a clear reading order to the rest.
4RTIACYL FO EAGSMSE → Clarity of message — When a viewer can state a visualisation's main point in seconds, thanks to a title that states the finding, no clutter, one message per visual and readable labels.
5FI AMNE != "" → if name != "" — An existence check tests that the user actually entered something, so the input is not an empty string. len(name) > 0 does the same job. Loop and re-ask until it passes.
6DIGIITS() → isdigit() — A type check method: returns True if a string holds only digits, so text can be rejected where a number is needed. The alternative is to put int(value) inside try/except.
7FI 0 <= AKRM <= 001: → if 0 <= mark <= 100: — A range check tests that a number lies between a minimum and maximum. This chained comparison is True only when mark is from 0 to 100 inclusive, so the boundary values 0 and 100 are accepted.
8FAICRNEIVTIO → verification — Checking that data was entered or copied exactly as it appears in the source, such as by double entry or comparing it with the original. It checks accuracy, not reasonableness.
9RGNDFAERIPOO → proofreading — Carefully reading text, labels and figures to find and fix spelling, wording and number errors before you publish your work.