VCE Data Analytics U4O1 Word Scramble: Manipulating data with software tools and Analysing data with statistics (Modules 3–37)
Name:
Date:
Class:
🔤
Word scramble
Unscramble the letters and write each key term on the line.
1
AEPTLMET
A pre-built file with the layout, formulas and formatting already set up, so new data can be entered quickly and consistently every time it is reused.
2
IA TORMPP
Instructions given to an AI tool. A good one states the data (field names), the chart or summary wanted, the audience and the format, using sample or de-identified data.
3
=302(BN:MXB)-A2B(3B:I0M)
Range is the largest value minus the smallest. It shows how spread out data is, but one outlier can stretch it. Not the same as a cell range like B2:B30.
4
IDMATAEIST.TTSS(ACNA)
The statistics module calculates descriptive statistics on a list: mean() is the average, median() the middle value, stdev() the spread. Use import statistics first.
5
IODNSBRUIITT HASEP
How values cluster and spread on a histogram: symmetric (bell-shaped), uniform (flat), or bimodal (two peaks), with gaps showing where few or no values fall.
6
KESW
Data with a longer tail on one side. The tail pulls the mean its way: a right tail is positive ______, a left tail is negative ______, and the median stays nearer the bulk.
7
ECASTRT TOPL
A chart with one dot per record, using two numeric fields as x and y. The cloud of dots shows if the variables are related, and a dot far from the rest is an outlier.
8
=RERGN1(ALCOER, AENRG2)
Returns Pearson's r, from -1 to +1, showing the strength and direction of the linear link between two equal-length paired ranges of data.
Answer Key
VCE Data Analytics U4O1 · Modules 3–37
1AEPTLMET → template — A pre-built file with the layout, formulas and formatting already set up, so new data can be entered quickly and consistently every time it is reused.
2IA TORMPP → AI prompt — Instructions given to an AI tool. A good one states the data (field names), the chart or summary wanted, the audience and the format, using sample or de-identified data.
3=302(BN:MXB)-A2B(3B:I0M) → =MAX(B2:B30)-MIN(B2:B30) — Range is the largest value minus the smallest. It shows how spread out data is, but one outlier can stretch it. Not the same as a cell range like B2:B30.
4IDMATAEIST.TTSS(ACNA) → statistics.mean(data) — The statistics module calculates descriptive statistics on a list: mean() is the average, median() the middle value, stdev() the spread. Use import statistics first.
5IODNSBRUIITT HASEP → distribution shape — How values cluster and spread on a histogram: symmetric (bell-shaped), uniform (flat), or bimodal (two peaks), with gaps showing where few or no values fall.
6KESW → skew — Data with a longer tail on one side. The tail pulls the mean its way: a right tail is positive skew, a left tail is negative skew, and the median stays nearer the bulk.
7ECASTRT TOPL → scatter plot — A chart with one dot per record, using two numeric fields as x and y. The cloud of dots shows if the variables are related, and a dot far from the rest is an outlier.
8=RERGN1(ALCOER, AENRG2) → =CORREL(range1, range2) — Returns Pearson's r, from -1 to +1, showing the strength and direction of the linear link between two equal-length paired ranges of data.