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Statistics and planning

Why knowledge in statistics is important ?

1) when quantitative data are involved in experiments it's important to know if the

measurements we have are of any significance

2) when planning an experiment we should know what data to be collected

Summarising data Mean median mode

Normal distribution If a frequency histogram is drawn from a large sample of data and if it

falls In to a symmetrical bell shaped graph it is known as hotmail distribution.

Standard deviation Gives the idea of how clumped the individual measurements are aroundthe mean value. If the standard deviation is higher the datA are more widely distributed.

67% of measurements within normally distributed data lie within +- 1 standard deviation .

95% within the range of mean - + standard deviation.

Significance levels ; decisions about the significance of the results of any statistical test are

based around the 5% significance level. Results are said to be significant if they occur less

than 5% of the time

If result is significant at the 5 % level you can reject the null hypothesis and accept the

alternative hypothesis.

Students t test

Do you want to look at the differences between measurements from two sites populations

treatments

Are you planning to replicate all your measurements at least 6 times at each site Have you

got time to do more than 15 samples Are your data normally distributed Use the mean asthe summary and test for the significance of any difference using the students test

Calculate the value of t against the critical value for the d.f ( na+nb -2)

Larger the t value more that there is a difference.

If calculated t value is greater than the critical value we can reject the null hypothesis and

accept that there is a significant difference between the means of the two treatments.

Mann Whitney u test

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Do you want to look at tests from to different sites Are you planning to tke 6-15

measurements from each site Your data can be summarised using the median Calc u1

value and U2 values using the formula

If the smallest u value is less than or equal to critical value then we accept that there is

a significant difference between the 2 median values. Statistician prefer for us to accept

significance by rejecting a nul hypothesis that there is no difference.

Only statistical test where the calculated value has to be smaller than the critical value.

Spearman rank correlation test

Do you want to look at the difference between two or more sites NO

Are you looking for some sort of correlation between two variables yes Calculat rs

If this value is greater than or equal to the critical value then we accept that there is asignificant correlation between the two variables if rs is positive it's a positive correlation

and if negative a negative correlation