Statistical Tests

• The Chi Squared test is used when testing whether a difference between observable and expected frequencies is significant
• A null hypothesis is one which determines no difference or significance between variables
• There is no difference between the frequency of woodlice found in dry versus wet areas
• the observed frequency is the collected data in the chi squared test
• the expected frequency is the sum of all data values ratiod accordingly
• degrees of freedom are calculated by the number of categories subtract 1 for the chi squared test
• If the Chi Squared value is less than the critical value, the null hypothesis is accepted - there is a more than 5% probability that the results are due to chance
• If the Chi Squared value is greater than the critical value, the null hypothesis is rejected - there is a less than 5% probability that the results are due to chance
• A larger sample size tends to have significant results
• Spearmans Rank is used to deduce whether a correlation is significant
• To calculate Spearmans Rank, you must calculate the difference between the ordered ranks squared before substituting into the formula
• The 'n' in the Spearmans Rank equation represents the number of data pairs
• The correlation coefficient can only be between 1 and -1
• The critical value for Spearmans Rank is calculated by the number of data pairs compared to a given table of values
• If the correlation coefficient is greater than the critical value then the null hypothesis is rejected - there is a less than 5% probability that the results are due to chance
• If the correlation coefficient is less than the critical value then the null hypothesis is accepted - there is a greater than 5% probability that the results are due to chance
• A T Test is used when determining if the difference between two means is significant
• The three values needed are the mean, standard deviation and number of data values
• The degrees of freedom for a T Test are calculated by adding the two total numbers of data values and subtracting 2: (n1 + n2) -2
• If the value of t is greater than the critical value then the null hypothesis is rejected - there is a less than 5% probability that the results are due to chance
• If the value of t is less than the critical value then the null hypothesis is accepted - there is a more than 5% probability that the results are due to chance
• If the p value is less than 0.05 then the results are significantly different