1.1 Statistical Analysis
Deduce the significance of the difference between two sets of data using calculated values for t and the appropriate tables.
A t-test is a statistical test used to compare two means (e.g. between a control group and an experimental group). It can be used to compare a null hypothesis against an alternative hypothesis. A t-test can be one-tailed (difference only) or two-tailed (difference and direction). Data is statistically significant when there is less than a 5% probability that the results are due to chance. This means that the P-value has to be less than 0.05 significance level. Population size is reflected by the degrees of freedom, which is reflected by the degrees of freedom, which is calculated as population size minus two.
Explain that the existence of a correlation does not establish that there is a causal relationship between two variables
Correlation describes the strength of a linear relationship between two variables (positive or negative). Causation describes the relationship between two variables, where one variable has a direct effect on another. Correlation does not indicate causation.
State that error bars are a graphical representation of the variability of data
Error bars show the spread of measurements around a central tendency. Error bars will usually show either: the range of data, the standard deviation, or the 95% confidence intervals.
Calculate the mean and standard deviation of a set of values
Data can be measured in one of three ways: nominal (named categories, mode), ordinal (ranked or relative data, median), Interval (on a scale or normally distributed, mean)
Explain how the standard deviation is useful for comparing the means and spread of data between two or more samples.
Data sets that have the same mean may not have the same degree of variation in data. As standard deviation measures the spread of data, it can be used to compare data sets. There can be identical means but different spreads of data. A higher standard deviation means there is greater variation in the data set, whereas a lower standard deviation means there is less.
State that the term standard deviation is used to summarize the spread of values around the mean, and that 68% of the values fall within one standard deviation of the mean.
Data which is normally distributed will exhibit a bell-shaped curve which is symmetrical around a central mean. 68% of data values fall within one standard deviation of the mean. 95% of data values will fall within two standard deviations of the mean. 99.8% of data values will fall within three standard deviations of the mean.
