Prepared by: Mgr. Radana Gurecká, PhD.

check the webpage of our institute, pinboardshttps://www.fmed.uniba.sk/pracoviska/teoreticke-ustavy/ustav-lekarskej-fyziky-biofyziky-informatiky-a-telemediciny-lf-uk/use official email address! › ....@uniba.sk

practical training› Prepare (task, procedure, physical principle),

Protocol (printed), Protection (coat, lab rules)› each absence must be appologized and

replacedprotocols› record sheet – signed by teacher after

measurement› protocol – hand not later than 1 week after

measurement› all sheets must be signed (header), including

attachements, sealed together› assesment – min. 20% each protocol, min. 70%

whole semester (if not – repeatedmeasuremenets in January)

2 continuous tests - min. 70% from each› 3 termssemestral work – voluntary, posiible to gain 5% to protocol assesmentexam – written and oral part› student is obliged to complete the regular

exam date by the end of the examination period of the winter semester!

Système International (d'Unités) - SImeter m lengthkilogram kg weight !!!second s timeampere A electric currentkelvin K thermodynamic temperaturemole mol amount of substancecandela cd luminous intesity

radian rad plane anglesteradian sr solid angle

derived – combination of base units› m2, kg/m3=kg.m-3, m.s-1, Hz=s-1, N= kg.m.s-2,

V=kg.m2.s−3.A−1,...prefixed

Y yotta 1024 1 000 000 000 000 000 000 000 000 septillion quadrillionZ zetta 1021 1 000 000 000 000 000 000 000 sextillion trilliardE exa 1018 1 000 000 000 000 000 000 quintillion trillionP peta 1015 1 000 000 000 000 000 quadrillion billiardT tera 1012 1 000 000 000 000 trillion billionG giga 109 1 000 000 000 billion milliardM mega 106 1 000 000 millionk kilo 103 1 000 thousandh hecto 102 100 hundredda deca 101 10 ten

– —- 100 1 oned deci 10-1 0,1 tenthc centi 10-2 0,01 hundredthm mili 10-3 0,001 thousandthμ micro 10-6 0,000 001 millionthn nano 10-9 0,000 000 001 billionth milliardthp pico 10-12 0,000 000 000 001 trillionth billionthf femto 10-15 0,000 000 000 000 001 quadrillionth billiardtha atto 10-18 0,000 000 000 000 000 001 quintillionth trillionthz zepto 10-21 0,000 000 000 000 000 000 001 sextillionth trilliardthy yocto 10-24 0,000 000 000 000 000 000 000 001 septillionth quadrillionth

measurement in physics has its limited precisioncomplete record › number, unit, error› x0 ± Δx Δx – absolute uncertainityΔrx = Δx/ x0 - relative(fractional) uncertainityΔ%x = Δx/ x0 . 100% - percentage uncertainity

Accuracy of measuring equipment› Can be provided by manufacturer› Estimation – half of the smallest division

Reading a scale – range, units, smallestdevision!!!

ng aaa ssssccccaaaaallllleeeee – rrrrraaaaannnngggggeee,, unon

y g qbe videdppppppppppppppppppprrrrrrrrrrrrrrrrrrrooooooooooooooooooovidevidevide by maaaaaaaaaaaaaaaaaaannnnnnnnnnnnnnnnnnnuuuuuuuuufaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaatttttttttttttttttttttttttttttttttttttttttttttttttttttttttiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiioooooooooooooooooonnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnn ––––––––––––––––––––––––––––––––––––––––––––––– hhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaallllllllllllllllllllllllllllllllllllllllllllllllllllffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff oooooooooooooooooooooooooooooooooffffffffffffffffffffffffffffffffffffffffffooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooooffffffffffffffffffffffooooooooooooooooooffffffffffffffffooooooooooooooooooffffffffffffffffff tttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttttthhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhheeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeee sssssssssssssssssssssssssssssssssssssssssssssssssssssssssssssmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaalllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllllleeeeeeeeeeeeeeeeeeeeeeeee

!!!!!!!!!

random errors › uncontrolable fluctuations› changes in temperature, pressure, voltage

changes...› we can reduce the impact of such

uncertainities by repeating measurements

systematic errors› instrumental – equipment imperfection,

improper calibration› methodical – incorrect work procedure› personal – imperfection of senses› shift to one side› can be eliminated or reducedgross errors (carelessness, mistake, exhaustion)

statistics ?!?!?!?presentation and interpretation of resultsbiomedical research, clinical trials...› which drug is more efficient?› does the treatment affect the disease?› which parameter is the best to asses risk?› ...

qualitative – non-numerical› nominal – cannot be sorted› ordinal – rank order, can be sorted

quantitative - numerical› continuous – any value from interval› discrete – only specific values

nominal› eye colour in class – blue, green, brown...ordinal› level of education – elementary, secondary,

...› disease state – mild, moderate, severe

Discrete› number of siblings

Continuous› height› glycemia

0 1 2 32,7

1,55 m 2,08 m1,8333 m

description of resultssummarysorting

in practice, we observe only sample (ofpatients,...)induction of results obtained in sample to populationstatistical tests, correlations, ...

what is the height of people in the class?average

sum all the measurements, divide by their number (number of students) mode – most frequent value

sample size(number of students)

i-th measurement, value(x1, x2, ...)

x

median – middle valueorder the measurementsfor odd n – middle value› 11 measurements – 6th valuefor even n – average of 2 middle values› 10 measurements – average of 5th and 6th

value

minimummaximumrange – difference between minimum and maximum

standard deviation (SD, sx)

standard error of the mean (SEM, sex)

...eventhough it looks similiar 170±5Repeated measurements of the samequantity, with unchanged conditions (to eliminate random errors) →standarddeviation calculated for this set of measurements works as an estimation of error of the measurement, describes theunaccurancyMeasuring the height of students in class –calculated SD describes variability in theclass, not the error!

variance

coefficient of variation

Important for transparent data presentationBasic rule – common sense – how many significant figures are relevant?First significant digit = first non-zero digitError/deviation usually expressed with max. 2 significant digitsThen, round the value itself to the same number of decimal placesRather keep more decimal places during calculations, then do the final rounding for the results (never in opposite way)

Average 167,6778 cmStandard deviation 5,3102 cm

Result (167,7 ± 5,3) cm

„Common sense“ method – we usuallymeasure high with accuracy ofcentimeters, or 1/10 of centimeter – that iswhy the results would be expressed with thesame accuracy

Presentation of results, outcomesTransparent, easy to readRevealing trends, relations, correlations

Perpedicular› X axis – horizontal, independent variable› Y axis – vertical, dependent variableLabeling axes – variable (quantity), unitsSame distance on axis – same interval ofvalues! (if not stated otherwise, i.e. logarithmic scale)Proper scale, range of axes – to show what we are interested in

0

10

20

30

40

50

60

70

80

90

100

150 155 160 165 170 175 180

Wei

ght (

kg)

Height (cm)

Weight dependence on heightGirls

Scatter plot withregression line

0

5

10

15

20

25

30

35

1 2 3 4 5 6 7 8 9 10 11 12

Wei

ght (

g)

Day of experiment

Weight of mouse

Line graph

0

20

40

60

80

100

120

140

160

180

200

Muži Ženy

Heig

ht(c

m)

Height men vs. women

Men Women

Column graphwith error bars

Average ± SD

145

150

155

160

165

170

175

180

185

190

Muži Ženy

Heig

ht(c

m)

Height men vs. women

Men Women

33%

56%

11%

Nutritional status of girls according to BMI

podhmotnosť

normálnahmotnosťnadhmotnosť

Pie chart – percentage

Underweight

Normalweight

Overweight

HistogramPolygone of frequency

• Frequencies of values sorted into classes, intervals

0

100

200

300

400

500

600

700

Num

bero

f pat

ient

s

Height [cm]

Height distribution

Šebeková K, Csongová M, Gurecká R, Krivošíková Z, Šebek J. Gender Differences in Cardiometabolic Risk Factors in MetabolicallyHealthy Normal Weight Adults with Central Obesity. Exp Clin Endocrinol Diabetes. 2018 May;126(5):309-315.

How not to get lost in data?How to save time?How to avoid mistakes?How to reveal errors? How to use MS Excel effectively(OpenOffice, LibreOffice...)

What is it good for?Office, clinical practice› Evidence of patient› Next check› Insurance, points, procedures – keeping

track› ...Everyday life› Energy consumption, household expenses...

Organizing dataLabeling rows, colums, unitsSorting and filtering dataBasic functions, own formulas...

KOZLÍKOVÁ K, MARTINKA J. Theory and Tasks for Practicals on MedicalBiophysics. Tribun EU 2010. ISBN 978-80-7399-881-3