769980
Description
Flashcards by sophietevans, updated more than 1 year ago
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Created by sophietevans
over 10 years ago
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| Question | Answer |
| When you see 'repeatability' and 'precision', which test should you be thinking of? | Standard error of the mean. |
| What is the calculation for standard error of the mean? | σ/√n standard deviation / √ no. of samples or measurements |
| Why 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. |
| How 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. |
| What 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. |
| What 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. |
| What test should you be thinking of when you see key words: repeatability/reproducibility? | Standard deviation. |
| What 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. |
| Define 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 |
| When 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. |
| What 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. |
| What 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. |
| What is the calculation for a 95% confidence interval? | 95% C.I. = μ ± 1.96 (σ/n) = true mean ± 1.96 x (standard error) |
| What is the calculation for a 99% confidence interval? | μ ± 2.576 (σ/n) true mean ± 2.576 (standard error) |
| If 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. |
| If 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. |
| When 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. |
| How 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. |
| Why 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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