VCE Data Analytics U3O1 Crossword: Artificial intelligence trends in data analytics and Testing databases, spreadsheets and visualisations (Modules 130–148)
Name:
Date:
Class:
✎
Crossword
Read each clue and write the matching term in the grid. Numbers in brackets show the letters in each word.
1
2
3
4
5
6
7
8
9
10
Across
- 3. Estimates a new y value for a given x by extending the trend of existing data, e.g. predicting next year's sales. It is less reliable the further x is beyond the known data. Word 1 of: =________(x, known_ys, known_xs) (8)
- 4. Compare every value, label and axis scale in an AI-generated chart with the original data, and look for invented figures, before you trust or use the chart. Word 2 of: Check _______ source data (7)
- 8. Smart tools inside everyday software, like Copilot in Excel, that suggest formulas and charts, answer plain-English questions and find insights automatically. Word 4 of: built-in AI ________ (8)
- 9. Comparing a chart's plotted values, category labels, totals and axis scale with the source data to confirm the chart shows the data accurately. Word 2 of: Chart ____________ (12)
- 10. Reviewing the AI's chart, then sending a follow-up prompt that names exactly what to change, such as labels, chart type or detail, and repeating until it is right. Word 1 of: ________ a prompt (8)
Down
- 1. Training a model on past data so it learns patterns and can predict outcomes for new data, such as a category (classification) or a number (numeric prediction). Word 2 of: _______ ________ (8)
- 2. Word 1 of the term in 1 Down: _______ ________ (7)
- 5. Checking the appearance of a visualisation, such as layout, alignment, readability, colours and labels, often with a checklist to spot problems. Word 2 of: visual __________ (10)
- 6. A rule built from past data, like a regression line, that uses the relationship between variables to estimate new values. A strong r makes the estimates more reliable. Word 1 of: ___________ model (11)
- 7. How much you can trust a prediction. It drops with small samples, outliers and predicting far beyond your data, so always state how uncertain the prediction is. (11)
Answer Key
VCE Data Analytics U3O1 · Modules 130–148
1L
2M
3F
O
R
E
C
A
S
T
4A
G
A
5I
N
6S
T
7R
A
C
N
T
8F
E
A
T
U
R
E
S
H
S
A
L
N
I
P
T
I
I
N
9V
E
R
I
F
I
C
A
T
I
O
N
E
C
S
B
G
T
T
I
10R
E
F
I
N
I
N
G
L
O
C
I
N
A
T
L
Y
Across
3FORECAST — Estimates a new y value for a given x by extending the trend of existing data, e.g. predicting next year's sales. It is less reliable the further x is beyond the known data. Word 1 of: =________(x, known_ys, known_xs)
4AGAINST — Compare every value, label and axis scale in an AI-generated chart with the original data, and look for invented figures, before you trust or use the chart. Word 2 of: Check _______ source data
8FEATURES — Smart tools inside everyday software, like Copilot in Excel, that suggest formulas and charts, answer plain-English questions and find insights automatically. Word 4 of: built-in AI ________
9VERIFICATION — Comparing a chart's plotted values, category labels, totals and axis scale with the source data to confirm the chart shows the data accurately. Word 2 of: Chart ____________
10REFINING — Reviewing the AI's chart, then sending a follow-up prompt that names exactly what to change, such as labels, chart type or detail, and repeating until it is right. Word 1 of: ________ a prompt
Down
1LEARNING — Training a model on past data so it learns patterns and can predict outcomes for new data, such as a category (classification) or a number (numeric prediction). Word 2 of: _______ ________
2MACHINE — Word 1 of the term in 1 Down: _______ ________
5INSPECTION — Checking the appearance of a visualisation, such as layout, alignment, readability, colours and labels, often with a checklist to spot problems. Word 2 of: visual __________
6STATISTICAL — A rule built from past data, like a regression line, that uses the relationship between variables to estimate new values. A strong r makes the estimates more reliable. Word 1 of: ___________ model
7RELIABILITY — How much you can trust a prediction. It drops with small samples, outliers and predicting far beyond your data, so always state how uncertain the prediction is.