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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)