1.1.1 Error bars = range ofdataerror bars" - the graphicaldisplay of a data pointincluding its errors(uncertainties / range ofdata).e illustrate for a data pointwhere (x, y) = (0.6 ± 0.1, 0.5± 0.2).he value of the data point,(0.6, 0.5), is shown by thedot, and the lines show thevalues of the errors.
1.1.1 Error barsan be used to showeither:•The range of thedata, OR•The standarddeviation.
1.1.4large value for S.Dindicates that there is alarge spread of values / thedata are widely spread.hereas, a small value for S.Dindicates that there is asmall spread of values / thedata are clustered closelyaround the mean.
1.1.5 The significance of thedifference between two sets ofdataHand Mean length (mm) S.D (mm)Left 188.6 11.0Right 188.4 10.9Difference : 0.2Interpretation of calculated data:SD much greater than the difference in meanlength.Therefore, the difference in mean lengthbetween left and right hand is NOT significant.Conclusion:The length of right and left hands are almostthe same.(The SD can be used to help decide whether thedifference between 2 means is likely to besignificant).
1.1.5 another example…Hand / foot mean length (mm) S.D(mm)Right foot 262.5 14.3Right hand 188.4 10.0Difference: 74.1Interpretation of calculated data:S.D is much less than the differencein mean length.Therefore, the difference in meanlength between right hands and rightfeet is significant.Conclusion:
1.1.5 t-testan be used to find outwhether there is asignificant differencebetween the twomeans of two samples.se GDC or computer to
1.1.5 t-testStages in using t-testand a sample Tableof critical values of tPlease refer page 2,Biology for IBDiploma, AndrewAllot.
1.1.5 t-test.g of the use of the t-test:and Mean length t critical valuefor t(P=0.05)eft 188.6mm 0.0822.002ight 188.4mm
1.1.5 t-test (anotherexample….).g of the use of the t-test:and Mean length t critical valuefor t(P=0.05)hand 188.4mm 23.32.005feet 262.5mm
1.1.6 Correlation (pg 23,h/book)orrelation is a measure of theassociation between twofactors (variables)orrelation does not implycausation.inding a linear correlationbetween two sets of variablesdoes not necessarily mean thatthere is a cause and effect