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Sample size
Sample size is the number of individual samples measured or observations made in a survey or experiment. Statistically it is represented by the letter n. In general, the larger the sample size, the more likely it is that your data will provide an accurate reflection of what you are trying to measure or test. An easy way to increase the validity of your data is to increase sample size. Sample size is not the same as replication, which refers to running complete duplicates of your investigation at the same time.
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Deciding on the sample size depends on several factors:
` How much time is available? Is your data collection restricted to ` Do you have the resources available to carry out the
measurements? This includes both equipment and people.
` How are you collecting the data? Data can be collected
continually using a data logger, but if it is collected manually, your design must accommodate taking fewer measurements.
` How much will your sampling cost? Your budget may limit how
many samples you can take. You may only be able to take one field trip, or buy reagents to analyse 10 samples.
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a certain time period or season?
The experiment above is investigating the effects of nutrient level on plant growth. The sample size is 5 (n = 5), there are three treatments (three nutrient levels) and four replicates (12 pots in all; not all are visible). The plot is randomised. Sample size should be large enough to provide reliable data but will be limited by the time and resources available.
Qualitative and quantitative data: What's the difference?
The site had still, black murky water with some boggy hummocks. Secchi depth was 0.3 m, water pH = 5.0, water depth 0.5-1.2 m, current velocity 0.2 cm/s. Plant species A made up 75% of the vegetation present. The site area was 40% vegetation and 60% open water.
QUALITATIVE DATA
QUANTITATIVE DATA
• Deals with descriptions • Details can be observed but not measured • Examples include; colour (e.g. eye colour), smell (pleasant/unpleasant), taste (sweet, sour, bitter), texture (rough or smooth), or sex (male, female).
• Deals with numbers (numerical values) • Data can be measured • Examples include; length, weight, speed, time, temperature, sound level, cost, etc.
Ways to collect qualitative data:
Ways to collect quantitative data:
• Observations where the data collected is non-numerical (e.g. recording behaviour) • Surveys and questionnaires with open ended questions • Interviews • Focus groups
• Experiments and investigations • Observations where the data collected is numerical (e.g. the number of cars driving past a school in 10 minutes) • Surveys and questionnaires with closed end questions
1. The description of the sampling site in this investigation contains qualitative and quantitative information. In the space below categorise the information into qualitative and quantitative data:
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2. Refer back to the experimental set up on the opposite page. In the experiment, the pots were arranged on a bench in the lab. In the space below, show how you might organise the pots to maximise the collection of unbiased data: