Table 1

Some basic guidance for understanding statistics

P valuesP means probability. Therefore, it represents the probability of an event occurring. It evaluates how good the data supports the null hypothesis.
  • High p values: your data supports the null hypothesis. This is generally shown as p value >0.5.

  • Low p values: your data does not support the null hypothesis. This is generally shown as p value >0.5.

CIThe CI is a value that we are fairly certain our sample mean lies within. Normally measured at 95%. If samples were taken on numerous occasions, we would expect that 95% would contain the sample mean. Five per cent of the intervals would not contain the mean.
  • A 95% CI has a 0.95 probability of containing the population mean.

Correlation coefficientsThe correlation coefficient measures the strength and direction of the relationship between two variables. The range of values for the correlation coefficient (called r) is between −1.0 and 1.0.
  • A correlation of −1.0 shows a strong negative relationship.

  • A correlation of 1.0 shows a strong positive correlation.

  • A correlation of 0.0 shows no relationship between the two variables.

The stronger the correlation, the closer the r will be to ±1. If r is positive, the variables are directly related. If r is negative, the variables are inversely related. The significance of the relationship is reported as probability (p values) telling the unlikelihood of no relationship (correlation coefficient r) in the sample.
  • The smaller the p value, the more significant the relationship.

MeanThe mean, often called the average, is a measure of central tendency. It is the sum of all the values in a data set divided by the number of samples. For example, if this is a data set:
1, 1, 2, 2, 2, 2, 3, 3, 4, 4, 5, 5, 5
the mean is ‘3’ (39/13). It is useful in describing the sample characteristics such as age.
ModeThe mode is a measure of central tendency (average). It is the value that appears the most. For example, if this is a data set:
1, 1, 2, 2, 2, 2, 3, 3, 4, 4, 5, 5, 5
the mode is ‘2’. There can be more than one mode which is known as bimodal.
  • The mode is used for categorical data and is helpful when we need to know the most common or popular category.

MedianThe median is a measure of central tendency (average). It is the middle value in a data set arranged in numerical order. For example, if this is a data set:
1, 1, 2, 2, 2, 2, 3, 3, 4, 4, 5, 5, 5
the median (middle) number is 3. You have as many numbers on one side than the other of the median number.
  • If you have an even set of sample data average the middle two this number will be your median.

SDThe SD is a measure of how your data are spread around the mean.
  • If your SD is small, your data are spread close to your mean value.

  • When the SD is large, your data are spread away from the mean value.