"A correlation between two variables means they vary together. A positive correlation means that high values of one variable are associated with high values of the other, while a negative correlation means that high values of one variable are associated with low values of the other." (Steve McKillup, "Statistics Explained: An Introductory Guide for Life Scientists", 2005)
"Accuracy is the closeness of a measured value to the true
value. Precision is the ‘spread’ or variability of repeated measures of the same value."
"Designing a well-controlled, appropriately replicated and realistic experiment has been described by some researchers as an ‘art’. It is not, but there are often several different ways to test the same hypothesis, and hence several different experiments that could be done. Consequently, it is difficult to set a guide to designing experiments beyond an awareness of the general principles." (Steve McKillup, "Statistics Explained: An Introductory Guide for Life Scientists", 2005)
"Even an apparently well-designed mensurative or manipulative experiment may still suffer from a lack of realism." (Steve McKillup, "Statistics Explained: An Introductory Guide for Life Scientists", 2005)
"Graphs may reveal patterns in data sets that are not obvious from looking at lists or calculating descriptive statistics. Graphs can also provide an easily understood visual summary of a set of results." (Steve McKillup, "Statistics Explained: An Introductory Guide for Life Scientists", 2005)
"Inaccurate and imprecise measurements or a poor or
unrealistic sampling design can result in the generation of inappropriate
hypotheses. Measurement errors or a poor experimental design can give a false
or misleading outcome that may result in the incorrect retention or rejection of
an hypothesis." (Steve McKillup, "Statistics Explained: An Introductory Guide
for Life Scientists", 2005)
"It has often been said, ‘There is no such thing as a perfect experiment.’ One inherent problem is that, as a design gets better and better, the cost in time and equipment also increases, but the ability to actually do the experiment decreases. An absolutely perfect design may be impossible to carry out. Therefore, every researcher must choose a design that is ‘good enough’ but still practical. There are no rules for this – the decision on design is in the hands of the researcher, and will be eventually judged by their colleagues who examine any report from the work." (Steve McKillup, "Statistics Explained: An Introductory Guide for Life Scientists", 2005)
"No hypothesis or theory can ever be proven - one day there may be evidence that rejects it and leads to a different explanation (which can include all the successful predictions of the previous hypothesis).Consequently we can only falsify or disprove hypotheses and theories – we can never ever prove them." (Steve McKillup, "Statistics Explained: An Introductory Guide for Life Scientists", 2005)
"One of the nastiest pitfalls is appearing to have a replicated manipulative experimental design, which really is not replicated." (Steve McKillup, "Statistics Explained: An Introductory Guide for Life Scientists", 2005)
"One way of generating hypotheses is to collect data and look for patterns. Often, however, it is difficult to see any pattern from a set of data, which may just be a list of numbers. Graphs and descriptive statistics are very useful for summarising and displaying data in ways that may reveal patterns." (Steve McKillup, "Statistics Explained: An Introductory Guide for Life Scientists", 2005)
"The essential features of the ‘hypothetico-deductive’ view of scientific method are that a person observes or samples the natural world and uses all the information available to make an intuitive, logical guess, called an hypothesis, about how the system functions. The person has no way of knowing if their hypothesis is correct - it may or may not apply. Predictions made from the hypothesis are tested, either by further sampling or by doing experiments. If the results are consistent with the predictions then the hypothesis is retained. If they are not, it is rejected, and a new hypothesis formulated." (Steve McKillup, "Statistics Explained: An Introductory Guide for Life Scientists", 2005)
"The unavoidable problem with using probability to help you make a decision is that there is always a chance of making a wrong decision and you have no way of telling when you have done this." (Steve McKillup, "Statistics Explained: An Introductory Guide for Life Scientists", 2005)
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