Practical & Maths Skills: Statistical Tests Flashcards
What are statistical tests?
- Statistical tests are used to analyse data mathematically
- You can be more confident in your conclusions, if they’re based on results that have been analysed using statistical tests
What kind of hypothesis do we have to use in statisical tests?
- You need to use a null hypothesis
- This hypothesis states that there is no significant difference or correlation between the things you’re investigating
How are null hypothesises proved or disproved?
- With each statistical test, you calculate a critical value
- If the critical value is greater than the critical value at a probability (P value) of 5%, then you can be 95% confident that the difference is significant and not due to chance
- This is called a 95% confidence limit
What is a Student’s t-test?
- Use the Student’s t-test when you have two sets of data you want to compare
- It tests whether there is a significant difference in the means of the two data sets
- If the value obtained from the t-test is greater than P value of 5%, then you can be 95% confident that the difference in means is significant and not due to chance
What is a null hypothesis like for a Student’s t-test?
- There is no significant difference between X1 and X2
What are conclusions like for a Student’s t-test?
• t < CV
- Accept null hypothesis – no sig. diff. between X1 and X2
- With 5% chance of error
• t > CV
- Reject null hypothesis – is sig. diff. between X1 and X2
- With 5% chance of error
What is a chi-squared test?
- Use chi-squared test when you have categorical data and you want to know whether your observed results are statistically different from your expected results
- If your result is larger than the critical value at P = 0.05, you can be 95% certain the difference between the difference between observed and expected results is significant and not due to chance
What is a null hypothesis for a chi-squared test like?
- There is no significant difference between the observed and expected values for all the categories
What are conclusions like for a chi-squared test?
• X^2 < CV
- Accept null hypothesis – no sig. diff. between O and E
- With 5% chance of error
• X^2 > CV
- Reject null hypothesis – is sig. diff. between O and E
- With 5% chance of error
What is a correlation coefficient?
- A correlation coefficient allows you to work out the degree to which two sets of data are correlated
- The Spearman’s rank correlation coefficient is an example
- It is given as a value between 1 and -1
- A value of 1 indicates a strong positive correlation
- 0 means there is no correlation
- -1 means there is a strong negative correlation
How do we evaluate the Spearman’s rank correlation coefficient?
- If your result is higher than the critical value at P = 0.05, you can be 95% confident that the correlation between the two sets of data is significant and not due to chance
What is a null hypothesis for the Spearman’s rank correlation coefficient like?
• rs < CV
- Accept null, the positive/negative correlation is not sig. and due to chance
- With 5% chance of error
• rs > CV
- Reject null, the positive/negative correlation is sig. and not due to chance
- With 5% chance of error
How do we compare p-values to significance levels?
- Compare p-value to significance level
- If p-value is lower than significance level, reject null hypothesis
- If p-value is higher than significance level, we fail to reject null hypothesis