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Significance of difference
Deduce the significance of the difference between two sets of data using calculated values for t and appropriate tables.
Here are some key ideas of significance of difference in IB Biology curriculum:
- Any significant difference between two data sets
- Calculate a “p-value”: The probability that there is no difference between the two samples
- High P values: Small differences (high probability there is no significant differences between results)
- P>0.05: There is no significant difference between the two samples
- P<0.05: There is a significant difference between the results
Here lists out the step converting a t-test result (t-value) to a p-value in IB Biology:
“Table of t-Values” Pg. 7 of textbook
- Work out the nos of degrees of freedom (DF)
- DF=total nos. of results – 2
- E.g. Sample 1 (9,5,4,3,2) Sample 2 (6,9,12,14,5): DF=10-2=8
- Go down the DF column in the table of t-values until you reach your DF score
- E.g. 8
- Read across until you get to the closest value that is smaller than your calculated t value
- Read down to the bottom row which gives you “p”
Correlation
Explain that the existence of a correlation does not establish that there is a causal relationship between two variables.
Usually in IB Biology, there are two tests for correlation:
- Pearson correlation coefficient (r): Continuous and normally distributed data
- Sperman’s rank-order correlation efficient (rs)
There are some key ideas of correlation in IB Biology curriculum:
- Perfect correlation relationship: the value for ‘r/rs’ is +1
- No correlation: value is 0
- Perfect negative correlation: Value is -1
- A correlation does not mean that there is a cause and effect relationship between two variables
- Further research would need to be done to see what other factors might be influencing the relationship
End of the topic!
Drafted by Gina (Biology)