experiment qs

Question 1

What is accuracy?

Answer 1

Def: How close a measurement is to the true value.

To analyse:
- suggest systematic errors (consistently false results in one direction that decrease accuracy)
- suggest changes to method

Improved by: Correcting for systematic errors or using calibrated equipment.

Question 2

Precision (def, how to analyse)

Answer 2

Def: How close repeated measurements of the same experimental group are to each other

(experimental group= not control group)

• refer to data of dependent variable
• analyse data from within experimental groups, not between
• look for random errors that decrease precision
• suggest changes in method that could improve precision

Question 3

validity

Answer 3

Whether the experiment truly measures what it intends to measure.

Improved by: Designing the experiment well, controlling variables, and using appropriate methods.

Question 4

quantitative vs qualitative data:

Answer 4

quantitative: numerical
tells you how much, how many, how often
e.g height of a person (e.g. 170 cm)

The number of students in a class (e.g. 25)

Temperature in degrees (e.g. 22°C)

qualitative: descriptive, tells you what something is like, can observe or describe
e.g The color of a flower’s petals: red, yellow, blue

The texture of a plant leaf: smooth or fuzzy

Question 5

repeatability vs reproducibility

Answer 5

repeatability
the precision obtained when the same or similar results are produced by the same student, using same method and equipment, under the same conditions in a short time frame

reproducibility
degree of agreement between results of experiment produced by different students, working underdifferent conditions, with different equipment at different times and with different methods
reproducible if yields same or similar results in equivalent conditions

Question 6

Define IV, DV, controlled variable

Answer 6

IV: variable that is changed by the experimenter

DV: variable that is being measured / changes as a result of changing the IV

controlled variable: variables kept constant (To ensure the change in the dependent variable is caused only by the change in the independent variable)

Question 7

What is an outlier?
Suggest some causes of outliers
How can they be managed in data analysis?

Answer 7

• result that is a long way from other results and seen as unusual

causes:
- personal errors
- sampling error
- data processing error
- measurement error
- experimental error
- natural differences between biological samples

• data should still be accounted for and analysed
• don’t include in average if the cause is identified
• include in average if cause is not identified to avoid experimenter bias

Question 8

what causes random errors and reduces precision vs systematic errors and reduces accuracy?

How to reduce impact of random and systematic errors?

Answer 8

random errors:
causes:
measurment instruments
improved by:
- mutiple trials and average results

systematic errors: methododology

Causes:
uncalibrated equipment or used incorrectly
flawed method

• cannot be improved by repeating experiment