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Science DATA

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Total cards: 24•Content version: v3•Public deck•Updated: 8/1/2026

Card preview (24)

#1
Front (Question)

Norminal Data

Back (Answer)

catogories are named eg. apple orange

#2
Front (Question)

Discrete data

Back (Answer)

only perticular values allowed, whole naumber

#3
Front (Question)

Continuous Data

Back (Answer)

any numeric value is allowed

#4
Front (Question)

Controlled Variables

Back (Answer)

element which is constant and unchanged throughout the course of the investigation.

#5
Front (Question)

quantitative data

Back (Answer)

Quantitative data are measures of values or counts and are expressed as numbers. (e.g. how many; how much; or how often).

#6
Front (Question)

qualitive data

Back (Answer)

Qualitative data are measures of ‘types’ and may be represented by a name, symbol, or a number code.

#7
Front (Question)

When should you use a column graph

Back (Answer)

Column charts are useful for showing data changes over a period of time or for illustrating comparisons among items

#8
Front (Question)

When should you use a pie graph

Back (Answer)

Pie charts make sense to show a parts-to-whole relationship for categorical or nominal data.

#9
Front (Question)

When should you use a XY scatter

Back (Answer)

displaying and comparing numeric values, such as scientific, statistical, and engineering data.

#10
Front (Question)

Interpret Data

Back (Answer)

the process of using diverse analytical methods to review data and arrive at relevant conclusions.

#11
Front (Question)

Independent variable

Back (Answer)

Something that will stay the same through out the experiment

#12
Front (Question)

dependent variable

Back (Answer)

A Dependent variable is what happens as a result of the independent variable.

#13
Front (Question)

accuracy

Back (Answer)

the quality or state of being correct or precise.

#14
Front (Question)

precision

Back (Answer)

the quality or state of being precise : exactness

#15
Front (Question)

nano

Back (Answer)

0.000000001

#16
Front (Question)

micro

Back (Answer)

0.000001

#17
Front (Question)

milli

Back (Answer)

0.001

#18
Front (Question)

kilo

Back (Answer)

1000

#19
Front (Question)

Mega

Back (Answer)

106

#20
Front (Question)

Giga

Back (Answer)

109

#21
Front (Question)

Tera

Back (Answer)

1012

#22
Front (Question)

Validity of Data

Back (Answer)

how well data values are consistent,

#23
Front (Question)

4.81m into cm

Back (Answer)

481

#24
Front (Question)

2.68kg into g

Back (Answer)

2680