Flashcards
Measures of variation
Flashcards do conjunto (19)
- 1When you see 'repeatability' and 'precision', which test should you be thinking of?Standard error of the mean.
- 2What is the calculation for standard error of the mean?σ/√n
standard deviation / √ no. of samples or measurements - 3Why is standard error a more precise measure of variability than standard deviation?Because it takes into account the number of observations/samples that make up a mean rather than just the standard deviation about that mean.
- 4How are standard deviations about a mean commonly represented? How could this representation be misinterpreted?Mean ± standard error
This does NOT mean that we are sure that the true mean figure lies between these limits - at best, assuming normality, there is a ~68% change that the true mean is between these limits.
It also does NOT mean that all the observations lie between these limits.
If these limits were being represented on a graph, they could be misinterpreted for confidence intervals. - 5What is replicability/repeatability?It is a measure of short term variation. It involves repeat measurements on the same items under the conditions e.g. same time, same experiment, same location, using same experimenter/observer. If the same biomedical scientist measured the pH of 6 samples of the same blood taken at the same time with the same equipment, one would expect the data to display repeatability.
- 6What is reproducibility?A longer-term measure of variation relating to whether or not the experiment can be replicated. It is how consistent a set of data is between occasions, on a larger scale, or using different experimenters/observers.
If two different biomedical scientists tested the pH of the same sample of blood taken at the same time using the same equipment and got consistent values, the data/experiment could be said to be reproducible. - 7What test should you be thinking of when you see key words: repeatability/reproducibility?Standard deviation.
- 8What is the calculation for standard deviation?σ = √(Σni = 1 (xi - x-bar)-squared ) / n-1
Minus the mean from each individual value to find the deviations. Square these. Total the squared values. Divide by the sample number -1. Square root the whole thing. This is your standard deviation. - 9Define coefficient of variation.The ratio of the standard deviation to the mean expressed as a percentage: (σ / x-bar) x 100. (Standard deviation/mean) x100
- 10When is it more appropriate to use coefficient of variation rather than standard deviation alone?Coefficient of variation makes variation 'unit-less' so it is very useful for comparing data with different means and standard deviations e.g. comparing the variability of count data and percentage data simultaneously.
- 11What are the two common ways in which standard error may be expressed graphically?In a bar chart, standard error bars will usually be added positively (i.e. mean + 1x standard error) to each bar as opposed to ±. In a scatter plot, ±standard error bars will usually be added to each point.
- 12What should you do if you want to be fairly sure that your error bar includes in the true value on a graph?The error bars should be at least: mean ± 2x standard error.
- 13What is the calculation for a 95% confidence interval?95% C.I. = μ ± 1.96 (σ/n)
= true mean ± 1.96 x (standard error) - 14What is the calculation for a 99% confidence interval?μ ± 2.576 (σ/n)
true mean ± 2.576 (standard error) - 15If you have a 95% confidence interval, what does that mean?It means that you are 95% confident that the true mean lies in this range.
- 16If you want to be more confident that your value falls within a given range, you will increase your interval. However, what are you sacrificing in order to do this?Precision.
- 17When can 1.96 (95%) and 2.576 (99%) not be used for calculating confidence intervals?When confidence intervals are being calculated for small samples i.e. <30.
- 18How do you find the correct value to use if you cannot use 1.96 (95%) or 2.576 (99%) to calculate confidence intervals?You look up a t value in the t table according to the proportion of 2.5% (0.025; for 95% C.I.) or 1% (0.005; for 99% C.I.) and n-1 degrees of freedom.
- 19Why can z values (i.e. 1.96 for 95% C.I.) not be used for confidence intervals for samples <30?Because the values are not likely to be normally distributed with a sample size this small, so adjusted values must be used which take into account the sample size (degrees of freedom).
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- From the week 10 Experimental Design and Analysis lecture.
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- sophietevans
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