AH Biology U3 KA2: Experimentation

Purpose of a pilot study

• help plan procedures

• assess validity

• check techniques

  This allows evaluation of experimental design. Pilot studies are integral to the development of an investigation.

  A pilot study can also:

• ensure an appropriate range of values for the independent variable

• allow the investigator to establish the number of repeat measurements required to give a representative value for each independent datum point

Independent and dependent variables can be

continuous or discrete

The experimental treatment group is compared to a

control group

Qualitative data

subjective and descriptive

Quantitative data

numerical data that can be measured objectively

Ranked data

data for which the observations have been replaced by their numerical ranks from lowest to highest

What is meant by simple experimental design and what are the pros and cons of this design?

• experiment where there is one independent variable

• pro: can be conducted more easily than in the field due to control of laboratory conditions

• con: findings may not be applicable to a wider setting

Multifactorial experimental design

• experiment where there is more than one independent variable, i.e. combination of independent variables or treatments

• investigators may use groups that already exist so there is no truly independent variable

Observational studies

• researcher observes and statistically analyses certain phenomena in order to assist in establishing new principles or discoveries

• the independent variable is not directly controlled by the investigator for ethical or logistical reasons

• pro: good at detecting correlation

• con: less useful for determining causation as they don't directly test a hypothesis

Confounding variables

• factors other than the independent variable that may affect the dependent variable, due to the complexities of biological systems

• must be held constant if possible, or at least monitored so their effect in the results can be accounted for in analysis

Randomised block design

• used when confounding variables cannot easily be controlled

• randomised blocks of treatment and control groups can be distributed in such a way that the influence of any confounding variable is likely to be the same across the treatment and control groups

Negative control

Provides results in the absence of a treatment, i.e. there should be no effect

Positive control

Treatment that is known to cause an effect, included to check that the experimental set up is capable of producing results.

Placebo control

Can be included as a treatment without the presence of the independent variable being investigated

Placebo effect

Measurable change in the dependent variables as a result of a patients expectations rather than changes in the independent variable

Define what is meant by in vitro and give pros and cons of this technique

• the technique of performing a given procedure in a controlled environment outside of a living organism

• e.g. cells growing in culture medium, proteins in solution, purified organelles

• pros: animals are not harmed, in vitro methods (e.g. organs in a chip, tissue and computer models) can sometimes more closely mimic what goes on inside the human body

• cons: difficult to predict more complex effects

In vivo

• experimentation using a whole living organism

• pros: can be used to predict more complex effects

• cons: can be expensive, animals may suffer as a result of testing, animal bodies not fully representative of human bodies

Representative sample

• used where it is impractical to measure every individual in a population

• should share the same mean and degree of variation about the mean as the population of a whole

Selection bias

The selection of a sample in a non-random way, so that the sample is not representative of the whole population

Importance of sample size

Sample size must be sufficient to decide without bias whether the change to the independent variable has caused an effect in the dependent variable

Error bars of treatment and control group do not overlap

Results are statistically significant and unlikely to have occurred due to chance

More variable populations require a

larger sample size

Random sampling

Members of the population have an equal chance of being selected

Systematic sampling

members of a population are selected at regular intervals

Stratified sampling

The population is divided into categories that are then sampled proportionally

Reasons for variation in experimental results:

• reliability of measurement methods

• inherent variation in the specimen

Determining reliability

• The reliability of measuring instruments or procedure can be determined by repeated measurements or readings of an individual datum point

• The variation observed indicates the precision of the measurement instrument or procedure but not necessarily its accuracy

The natural variation in the biological material being used can be determined by

The natural variation in the biological material being used can be determined by measuring a sample of individuals from the population

mean of repeated measurements

Gives an indication of the true value being measured

Range of values

a measure of the extent of variation in the results

Describe how independent replication is carried out

• Independent replicates should be carried out by researchers who were not part of the original research group to produce independent data sets

• These independent data sets should then be compared to determine the reliability of result

• Overall results can only be considered reliable if they can be achieved consistently

Correlation

Relationship between two variables but does not imply causation

Causation

The changes in the values of the independent variables are KNOWN to cause changes to the value of the dependent variable

Accuracy

A description of how close a measurement is to the true value of the quantity measured.

Validity

The ability of a test to measure what it is intended to measure

Precision

The degree to which repeated measurements show the same result.

Reliability

Ability of a test to yield very similar scores for the same individual over repeated testings