SCIENTIFIC SKILLS Flashcards
1
Q
true value
A
The value that would be found if the quantity could be measured perfectly.
2
Q
accuracy
A
- it is judged to be close to the true value of the quantity being measured
- Accuracy is a qualitative term; a measurement value or measurement result may be described, for example, as being ‘less accurate’ or ‘more accurate’ when compared with a true value.
Only quantitative data can be described as accurate since quantitative data is repeatable and measurable.
3
Q
precision
A
- A measure of the repeatability or reproducibility of scientific measurements
- refers to how close two or more measurements are to each other.
- A set of precise measurements will have values very close to the mean value of the measurements.
- Precision gives no indication of how close the measurements are to the true value and is therefore a separate consideration to accuracy.
4
Q
measurement results
A
- Refers to a final result, usually the average of several measurement values.
- In the (unusual) case where only one value has been measured, then measurement result also applies to that single measurement value.
- taking an average measurement is appropriate when data is close together with no outliers
5
Q
repeatability
A
- The closeness of the agreement between the results of successive measurements of the same quantity being measured, carried out under the same conditions of measurement.
- same observer, same measurement procedure, same measuring instrument used under the same conditions, the same location, and replicate measurements on the same or similar objects over a short period of time.
- Experiments that use subjective human judgement(s) or that involve small sample sizes may yield results that may not be repeatable
- Repeatability can be used to evaluate the quality of data in terms of the precision of measurement results.
- Ideally, measurements should be repeated where possible to produce a measurement result.
6
Q
reproducibility
A
- The closeness of the agreement between the results of measurements of the same quantity being measured, carried out under changed conditions of measurement.
- These changed conditions, involving replicate measurements on the same or similar objects,
- include a different observer, different method of measurement, different measuring instrument, different location, different conditions of use and different time.
- The purposes of reproducing experiments include checking of claimed precision and uncovering of any systematic errors that may affect accuracy from one or other experiments/groups.
- Experiments that use subjective human judgement(s) or that involve small sample sizes or insufficient measurements may also yield results that may not be reproducible
- Reproducibility links closely to the accuracy of an experiment. Reproducibility can also be used to evaluate the quality of data in terms of the precision of measurement results.
7
Q
resolution
A
- The smallest change in the quantity being measured that causes a perceptible change in the value indicated on the measuring
- This has implications for determining the number of decimal places to which a quantity may be quoted
- if the measurement scale on a 50 mL burette is at 0.1 mL intervals, the resolution of the burette is said to be 0.1 mL.
- In a titration, the user must estimate the volume between the two marked intervals on the burette so that the value reported will be to two decimal places
- measurement readings of 10.50 mL or 10.55 mL are possible, but a measurement reading of 10.53 mL cannot be claimed.
- The meniscus of the liquid will either be on the burette line marking, in which case the reading would be 10.50, or it will lie between 10.50 and 10.60, in which case it is measured as 10.55 mL.
smallest increment of a scale
8
Q
validity
A
- A valid experiment investigates what it sets out and/or claims to investigate.
- Both experimental design and the implementation should be considered when evaluating validity
- An experiment and its associated data may not be valid, for example, if the investigation is flawed and controlled variables have been allowed to change.
- Data may not be valid, for example, if there is observer bias.
9
Q
random errors
A
- Affect the precision of a measurement and may be present in all measurements.
- Random errors are unpredictable variations in the measurement process and result in a spread of readings.
10
Q
systematic errors
A
- Cause readings to differ from the true value in a systematic manner so that when a particular value is measured repeatedly, the error is the same.
- Systematic errors result from limitations in the instrument itself or incorrect calibration, or inappropriate methods (including parallax).
11
Q
repeated measurements
A
Are made to reduce the effect of random errors (and reduce the likelihood of mistakes).
12
Q
mistakes
A
- Sometimes called personal errors
- Mistakes should not be included in reporting and analysis as part of the ethical consideration of data handling.
- Rather, the experiment should be repeated correctly.
13
Q
uncertainty
A
- The uncertainty of the result of a measurement reflects the lack of exact knowledge of the value of the quantity being measured.
- errors associated with the calibration of a piece of equipment,
expressed as ± after the value
14
Q
significant figures
A
- all digits in numbers expressed in standard form are significant: for example, 4.320 x 10 has four significant figures
- all non-zero numbers are significant: for example, 42.3 has three significant figures
- zeros between two non-zero numbers are significant: for example, 4.302 has four significant figures
- leading zeros are not significant: for example, 0.0043 has two significant figures
- trailing zeros to the right of a decimal point are significant: for example, 42.00 has four significant figures
- for numbers less than one, 0.4 has one significant figure and 0.04 also has one significant figure, whereas 0.40 has two significant figures and 0.400 has three significant figures
- whole numbers written without a decimal point will have the same number of significant figures as the number of digits, with the assumption that the decimal point occurs at the end of the number: for example, 400 has three significant figures. Therefore, a stated volume of ‘400 mL’ will be considered as having three significant figures.
15
Q
outliers
A
- Data points or observations that differ significantly from other data points or observations are sometimes called outliers.
- Outliers in data must be further analysed and accounted for, rather than being automatically dismissed, as an ethical approach to dealing with data.
- Repeating readings may be useful in further examining an outlier: for example, to determine whether the outlier is a personal mistake.
