Exam tech Flashcards

1
Q

give/state/define/identify

A

simple recall of facts or definitions

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2
Q

describe/outline

A

say WHAT happens in a process or graph or results (but NOT why)

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3
Q

explain

A

say HOW or WHY something happens in detail

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4
Q

illustrate

A

explain (how and why) using EXAMPLES (based off no. of marks)

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5
Q

summarise

A

describe AND explain MAIN POINTS

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6
Q

compare

A

similarities AND differences

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7
Q

evaluate/discuss

A

give advantages AND disadvantages followed by summary/statement/opinion

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8
Q

quality

A

does support AND does not support

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9
Q

justify

A

pros AND cons followed by SUMMARY STATEMENT (usually to explain why something already happens or takes place in the way it does)

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10
Q

suggest

A

use knowledge and apply to an unfamiliar example

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11
Q

conclude

A

make decision about something (no. of marks indicates no. of conclusions)

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12
Q

analyse

A

explain AND evaluate/justify THEN conclude (use data and figures if necessary)

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13
Q

five specific ways of “moving”

A
  • diffusion
  • facilitated diffusion
  • active transport
  • co-transport
  • osmosis
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14
Q

when can the word “transport” be used?

A

when talking about vesicles or organelles moving within a cell (active movement)

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15
Q

how are chonromsomes and chromatids “moved”?

A

“pulled” by spindle fibres

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16
Q

six things to talk about in “describing graphs”

A
  • rate of change
  • shape of curve (exponential, sigmoid, proportional etc)
  • plateau
  • fluctuations
  • origin of graph (where does the change start)
  • use data/ % changes
17
Q

how can graphs be split up?

A
  • no. of marks = number of parts
    OR
  • initial trend, change in tend, final trend (three parts)
18
Q

how can data tables be split up?

A
  • initial trend
  • change in trend
  • final trend

(usually look at means)

19
Q

how to “describe data”

A
  • describe different trends
  • calculate differences within a group of results
  • calculate differences between groups of results
  • calculate % change
  • identify anomalies
  • make a concluding statement if it says conclude
20
Q

“use the figure” vs “use the figure and your own knowledge”

A
  • use the figure ONLY accepts information from the figure
  • and your own knowledge requires points from the figure and points NOT INCLUDED in question
21
Q

why are repeats taken?

A
  • IDENTIFY anomalies
  • calculate means (without anomalies)
  • reduce % error
22
Q

why is reproducibility important?

A
  • enables peer review
  • signifies a workable method
23
Q

why is validity important?

A

ALL variables controlled meaning other factors affecting results are ruled out

24
Q

how can validity be improved?

A
  • having an experimental control
  • controlling all variables
25
two types of experimental controls and what they are
- positive (a known response is expected) - negative (no response is expected)
26
example of a positive and negative control in the investigation of a new acne medication
negative: - control group given placebo (no result expected) positive: - control group given a pre-existing medication with a known and measurable effect - compare effectiveness
27
how would you "explain how you can ensure confidence in results"
describe ways (such as variables, sample size, repeats) that the data is: - repeatable - reproducible - valid - stats test
28
plan an investigation
- control variable AND specifically why (validity) - comparable (initial and final) dependent variable (quantitative or qualitative and why?) - independent variable - control experiment (positive or negative) AND why (validity) - give an exact sample size (repeatability) - give an exact number of repeats (repeatability) - potential ethical concerns - calculate a standard deviation to measure spread of results - use a specific stats test to prove the significance of any results
29
two types of error
- systematic error - random error
30
what is needed to identify error?
- mean OR - expectation of true results
31
how can types of error be determined?
random error: - anomalies are far from mean - anomalies are random rather than close together systematic error: - anomalous results are way outside of true data/mean - anomalous results occur in a predictable way/could be close together