Exam tech

Question 1

give/state/define/identify

Answer 1

simple recall of facts or definitions

Question 2

describe/outline

Answer 2

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

Question 3

explain

Answer 3

say HOW or WHY something happens in detail

Question 4

illustrate

Answer 4

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

Question 5

summarise

Answer 5

describe AND explain MAIN POINTS

Question 6

compare

Answer 6

similarities AND differences

Question 7

evaluate/discuss

Answer 7

give advantages AND disadvantages followed by summary/statement/opinion

Question 8

quality

Answer 8

does support AND does not support

Question 9

justify

Answer 9

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

Question 10

suggest

Answer 10

use knowledge and apply to an unfamiliar example

Question 11

conclude

Answer 11

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

Question 12

analyse

Answer 12

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

Question 13

five specific ways of “moving”

Answer 13

• diffusion
• facilitated diffusion
• active transport
• co-transport
• osmosis

Question 14

when can the word “transport” be used?

Answer 14

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

Question 15

how are chonromsomes and chromatids “moved”?

Answer 15

“pulled” by spindle fibres

Question 16

six things to talk about in “describing graphs”

Answer 16

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

Question 17

how can graphs be split up?

Answer 17

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

Question 18

how can data tables be split up?

Answer 18

• initial trend
• change in trend
• final trend

(usually look at means)

Question 19

how to “describe data”

Answer 19

• 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

Question 20

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

Answer 20

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

Question 21

why are repeats taken?

Answer 21

• IDENTIFY anomalies
• calculate means (without anomalies)
• reduce % error

Question 22

why is reproducibility important?

Answer 22

• enables peer review
• signifies a workable method

Question 23

why is validity important?

Answer 23

ALL variables controlled meaning other factors affecting results are ruled out

Question 24

how can validity be improved?

Answer 24

• having an experimental control
• controlling all variables

Question 25

two types of experimental controls and what they are

Answer 25

- positive (a known response is expected) - negative (no response is expected)

Question 26

example of a positive and negative control in the investigation of a new acne medication

Answer 26

negative: - control group given placebo (no result expected) positive: - control group given a pre-existing medication with a known and measurable effect - compare effectiveness

Question 27

how would you "explain how you can ensure confidence in results"

Answer 27

describe ways (such as variables, sample size, repeats) that the data is: - repeatable - reproducible - valid - stats test

Question 28

plan an investigation

Answer 28

- 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

Question 29

two types of error

Answer 29

- systematic error - random error

Question 30

what is needed to identify error?

Answer 30

- mean OR - expectation of true results

Question 31

how can types of error be determined?

Answer 31

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

Question 32

what should you not say when referring to T killer cells?

Answer 32

DON'T say kill cells, instead say that they attack damage cells

Question 33

general things to mention when evaluating a conclusion

Answer 33

- sample size - name other factors that may affect results - correlation doesn't mean causation - use data or examples from figures etc - have SD/stats tests been used?

Question 34

how would you "refine a method"

Answer 34

- add specific details of method e.g. volumes, times, concentrations - add more control variables and how you would control them - extra steps like stirring etc

Question 35

when answering "what might have caused the inaccuracy of this result?", what would and wouldn't be a suitable answer?

Answer 35

suitable: error that couldn't be avoided not suitable: human error that could be avoided

Question 36

what should you make sure not to say when drawing a conclusion?

Answer 36

- don't use the word "cause" as this implies correlation = causation - don't make implications, state directly what is shown without making assumptions e.g. the graph shows that methyl jasmonate increases final mass of tomato plant RATHER THAN methyl jasmonate reduces herbivory

Question 37

why might modes or medians be better at representing information than means?

Answer 37

modes and medians are less affected by anomalies that means

Question 38

what word should you use when referring to breeding in artificial selection?

Answer 38

use crossbreeding (not inbreeding)