Table Of ContentSection 3: Work, Energy and Power Section 2: Waves
1. Work and Power 101 1. Progressive Wave.~ 186
2. Kine-lie Energy and 2. Frequency, Speed and Intensity 190
Gravitational Po1ential Energy 105 J. Electromagnetic Waves 194
3. Conservation of Energy 107 4. Polarisation 196
Exam-style Questions 112 5. Reflection and Refraction 199
Introduction Module 2 6. Refractive Index and
Section 4: Materials T00tl lncernal Reflection 202
1--low 10 use this book Foundations of Physics 1. J-looke's law 113 7. Superposition and lntederence 207
I. Quantities and Units 30 2. elastic and Plastic Defonnation 118 8. Diffraction 211
2. Making Estimates 34 3. Stress and Slrain 122 9. Two-Source Interference 213
3. Errors and Uncertainties 36 4. lhe Young Modulus 124 10. Young's Doublc..'-Slil Experiment 216
II
4. Graphical Representations of Unccnainties 39 5. Stress-Strain Graphs 127 11. Diffraction Gratings 220
How Science Wor1<s 5. Scalars and Vectoo; 41 Exam-style Questions 133 12. Stationary Waves 223
Ex.tm-style Questioos 47 Exam-style Questions 229
The Scieniific Process
Section 5: Newton's Laws of Motion
and Momentum Section 3: Quantum Physics
1. Newton's Laws of Motion 135 1. The Photon Model 232
2. Momentum 138 2. The Planck ConstanL 234
Module3 J. Impulse and Vehicle Safety 142 J. The Photoelectric Effect 237
Module 1
Exam.style Questioos 147 4. Wave-IMide Duality 241
Section 1: Motion Exam-style Questions 246
Development of Pracllcal Skllls
t. Consrant Acceleration 48
I. Planning an Expcrimen1 5 2. Acceleration Due To Gravity 50
2. Rl!Cording and Processing Da1a 9
3. Projectile Mocion 53
3. Presenting Results 11 4. Displacemem-lime Graphs 55 Module4
4. Analysing Results 13 5. Velocity-lime Graphs 60 Module 5
5. Evaluating and 6. ln\!estigating MOfion 66 Section 1: Electrlclly
Drawing Conclusions 16
Exam-style Questions 22 7. Slopping Dislances 70 1. Circuit Diagrams 149 Section 1: Thermal Physics
Exam-style Questioos 73 2. Current 150 1. rhases of Matter and Temperature 248
3. Potential Difference 153 2. Thermal Propenies of Ma1crials 252
Section 2: Forces In Action 4. Resistance and Resistivil'y 155 3. The Gas Laws 257
- I .•v tass, \.Vcight and Force Basics 76 5. Types of Conductor 159 4. The Ideal Gas equation 262
Practical Skills 2. Not forces 79 6. 1-V Characteristics 162 5. The Pressure of an Ideal Gas 264
3. Equilibrium 82 7. Power and Eleclrical Energy 165 6. lntornal Cnorgy of an Ideal Gas 267
Practical Skllls for the 4. Momenls and Torques 85 8. Domcslic EJecuicity 168 Exam.style Questions 271
Practical Endorsement 5. Drag and Terminal Velocity 90 9. E.mJ. and Internal Resistance 170
I. General Practical Skills 23 6. Density, Pressure and Upthrust 94 10. Consecvation or Energy
2. fUo.'Cping Scientific Records 26 Exam..tyle Questions 98 and Charge in C:ircuirs 175
11. The Potential Dfvider 179
3. Practical Activity Groups 28
Exam-style Questions 183
Section 2: Circular Motion and Section 2: Electrlc Fields Maths Skills
Osclllatlons 1. Cloclric llclds 368
I. Orcul.ilr Motion 273 2. Unifonn Clooric n.,lds 372 I Cllculations 471
2. Cmoripcul Fon:e and M:ook>rnoion 276 3. El«lric 1"4Mllal 374 2. Afgd>ra 476
J. Simple! f larmonic Motion 280 4. ComP"ring I i<'ct1ic 3.Graphs 478
4. C:.1lculations \Vith SMM 284 and Cr:wl1a1ional riclds 377 4. 1x poncntiaf and log Graphs 483
5. lnvt_'SliJ;.11ing 5HM 287 Exam-slyle Qu.,lions 379 5. Gl'OOlClry and Trigonomcory 485
6. Jr ro and l"Orccd Oscillations 290
fxam. .t yle Questions 295 Section 3: Electromagnetlsm
I. MagllC'llC I IC'lds 381
section 3: Gravitational Fields 2. Magnc<lc 1 lux Densily 384
1. Gr:Ml3llonal FK!kls 297 3. r«a>s on Ch.vJ:<'d r.uticlcs 389 Exam Help
2. Gravil31JOnal Ficld Sm!ngth JOO 4. M:tgn<lic I lux •nd Flux linkage 394 r lClm Structure and Technique! 489
3. Gr:av1l3l100.1l PIJlmtial and Cnorgy 303 5. Farad:!)"$ I aw •nd lmz's law 398
4. Molion ol Masses in Gravi1a1ional ll<'lds l08 6. Uses ol I i«:tromagnctic Induction 403
fxam. .t yle Questions 313 fxam-slyle Qu. .t ions 409
section 4: Astrophysics Section 4: Nuclear and Particle Reference
and Cosmology Physics
I . 1l1C' Sola1 System 315 I. Alomic Structure 411 """""" 492
2. l\Slronomical Distances 317 2. 100 Nuclros 415 Glossary 550
3. Slcll3t Cvo1ution 320 3. r.uticl<s •nd An11p;111idcs 419 Ad<nowlcdgcmmts 562
4. Srcllar 1Qdia1ion and Luminosity 324 4. Quatlcs and Anli.quor1cs 424 lnd<>x 564
5. Stellar Spcclra 328 5. Radiooctlvt! °"°Y 427 0313 T:iblcs 572
6. 1l1C' Big llong Thco<y 333 6. Nucl<'31 J)J>ciy Cqualions 431
7. lhc• I voluoion of 1he Universe 338 7. Cxpoll<'llllal i aw of Decay 433
fxam. .t yle Questions 343 8. Malf-llr~ ond RJd1oactiV4> Oaling 437
9. i!indlng I ""'BY 442
10. Nuc~ar I ission and rusion 445
11. llsslon R~""'°" 449
Wm-style Que<lions 4SJ
Module&
Section s: Medical Imaging
Section 1: Capacitors
I. X-rny imag1111 456
I. C:>pacilO<S 346 2. Mcdicil ll«'S or Nuclca1 Radiation 460
2. C:1pacitors in CircuilS 351 3. Mcdic-'ll USC" or Ultrasound 463
J. ln\<t_'Slii;.11ing Charging and Exam-style Qu.,lions 469
l)isc.hnrging Capacitors 356
4. Chorging and Discharging C.lculaolons 360
wm. .t yle Questions 366
l
., 'mu nood 10 know abou1 t low Sclonco
Works. There's a sedi<>n on it at the
fronl of the book.
(@HOW
How Science Works is also
Learning Objectives COV<!ft!d throughout lhc ~~
''°""""""'
Tlehaersne, oterl lb )e'W ob kC>l O10ld dlyo ,w lhoarl t hyoo uc l"Q"m"'1. 10 :5.!-- ; tbhoiso kS )mboi. )'W """ ~-
----
llll're's a spccifoc;itoon R'fe<rocc "' 11><>
bollom Iha! links IO the OClt A lpC'Ciflci1lon. ~-
:-:;~=--- Practice Questions - Appllcatlon
Annoyingly, the c...mi,..,,. CXpccl you 10
Tips and Exam Tips __ be able IO apply }'JU' knowlcq;c 10 new
1hore ""'lips lhroughoul siluations - lhcsc qu<'51ions •re heft' 10
the boolc 10 help with •II ·..-.. _-· ~. .. )'W plcnly ol pr.IC1IC<! •I doing this.
SOr1S ol thor.is. including ·~....-........-.--- All the a<>S>\'ers arc in lhc bode ol 1he
exam 11ps so do '""h boolc (including any calcula1lon woric.mgs~
answcri ng "'""" qu<'SllOflS. __
......
,........,_ ... •·~ :=;=-:~.:,,--..-.-. ----.-.-.-.....,- .
·~~...,..,;..._ :.~ __ ~~
.....: -:.:;-...:.=----.. - _..._. Practice Questions - Fact Recall
Maths Skllls
llll'rc art! a IOI of facts you need 10
Tmcthxhaaperlc lcrseeehlde'os dwu. rp1 a0t hln i•ekspsecep o tlmhy(i msai.nl ha Tytsh hosseku rsirel kle'ssixl laisanm ls yaoose .u at i ctomxonaau m1:l:hdpis~ k b >cs --·~-.·4.-.. .C... ..U..::, .:•. C ...,:..>......_..-_..' -. U..- . _l.•-_._. (.) ....._..... .u >. ....•.. _• •- l· llAeola ll retnhs et- lahnalhsl wc)"sOecUr sq kuanerocsw tiino t nh1she cam rbc.a chke o~ l
skills scelion a11hc back ol 1h<• boolc. ~----1-...c:=:::'--•-' • te·~JJP:" ~lo•"I lhebook.
-·-,----
Exam-style Questions
_
___ ... IT-lf11sln.g f')(am.sty~ questions is really
.~.. haracteristics lm1x>nan1- you'll Ond some al 1he end of
--·~"····-·---- c•ach SN11on. -
-W:...: h_..a..l_ ".,,:.-. ". 1 ..'v-.c-i.:w... ._.,c.~.1..·t:~.t1:s.u.:c~ 1:?. .~ ·"n' -:'.,J--:- --+--1 Examples sTehto Iyn'r ott wth orc s:inl m<'oxa Sm1sy le- ass tohme eo nweisll yteosut 'yllo ur t ..,a,_ .·• ..-.•_. 1-•-_-.-.. •_.... ._• ,•._ . .. ...,.. •.1.•.·...- ·~-·
·y Those are here 10 help you knowlodgo and undmianding and some ·-
/_.·-:~?.i undooaand the d>00ry. wlll ocst 1hat you can apply your knowledsc. ....·.-...- _-_-_- _... __
_
_~__ .. ___ --__· ~- aAllol n1gh cw ainths wae mrs.i oaircc s icnh 1mh1ec b 1a0c ksh oofw! h yeo buo hookw, ' -------.......--......- . ·-
"""" ,...,
you got lhc m.>rks.
Practical Activity Groups
'°1'11 nood 10 show you've -00
sfnocmloer sk<emy epnrLac tlincfaol nsknialtlslo inn oynou thr eP rskaic1t1ics al Exam Help ...._....,.. __ __ ·-
-----~--··-~ 1yhwro on oaored manaodlc oepdp 1o4n' 1uhnrioliuegsh toou alp thpley b ook. Tstuhfrf<<'\d'' slu. lSl Co'lC 1liholnn"g's l ht<o> h bexlplc w oEi1l h1 hyeo buoroJ elcx am s. • --__.-..._.. _-._.._- -,-. _.. ·.- ._ u--_---__--__--__-__---__--. _.·_ ·. .- · ·
$--:~ ---- ..__ ·-
-= ------------ -....-....-.. &-llP_-....-._. ... _._a -
... Glossary
~.--.. ~-----~~-------- Truhnc onl- U'$S. <g'lluols ws3oiryu 3sl- thep <b'3lfd«ct o rol1r hloeo blcoionkg ~--------
up kry words and thrir mr.1nings.
~ -·-'~
IM
Published by CGI'
Editors:
Keith Blackhall, Ellen Burton, Eleanor Crabtree, Mary Falkner, Emily Forsberg. Rob Hayman,
Sharon Keeley-Holden, Camilla Sheridan and George Wright
Contributors: The Scientific Process
Tony Aldridge, Jane Canwright, Peter Cecil, Mark Edwards, Barbara Mascetti, John Myers, Zoe Nye,
Moira Steven and Andy Williams.
Science rries to explain how and why ihings happen. /i's all abour gaining
kno~vledge about Lhe lvorld. Scienrists do this by asking quest.ions, suggesting
annvers and I.hen doing tests to see if rhe(re correct - lhc scienlific process.
Developing and testing theories
A theory is a possible explanation for something. Theories usually come
aboul when scientists observe something and wonder why or how il happens.
Scientists also sometimes form a model too - a simplified picture or Tip: A theory is only
scientific if il can be
representation of a real physical situation. Scientific theories and models are
tested.
developed and tested in the follow·ing way:
Ask a question - make an observation and ask why or how wbatcvcr
you've observed happens.
Tip: The results of one
SuggesLa n anS\ver, or par1 of an anS\ver, by forming a theory or a model.
tesl can't~ that a
Make a prediction or hypothesis - a specific Lestable statemenL, based theory is true - they
on the theory, about what will happen in a test situation. can only~ that il's
true. They can however
Creafrurtye oitu (th Leelpst st o- dtisop prorovvei idt)e. evidence thal \1\'ill support the hypothesis or disprove a thoory
show that it's wrong.
Example
Question: What slops beta radiation?
Theory: Beta radiation will be stopped by a S mm thick sheet of aluminium.
Hypothesis: If bela radiation is stopped by a S mm thick sheet of aluminium
a Geiger-MUiier tube and counlcr will not detect radiation from a beta
source if the aluminium sheel is placed between the source and I.he mbe.
Test: Measure the background radiation count rate using the Geiger-MUiier
Lube and counter without a source present. Then, place a beLa-emiHing
source in front of the tube. Record 1he ne\v count ra1e. Then, place a S mm
f'Hll.QIO'f,llf'l.
Lhick sheet of aluminium between the source and the tube and once more TI\ /\ N S /\ C: TI 0 N $•
record the counl rate. If Lhc count rate has dropped to a level similar ........ 1011111
A CC OMP1
to the background count rate, then Lhe beta radiation emitted by the
..................
source has been absorbed by the aluminium sheet, and this evidence •• '•I 't.11 t II'
~
With thanks to Emma Clayton and Sarah Williams for the proofreading. supports the hypothesis. ..0. ,. .f .I.ll
t N OE N I OUS
With thanks to Jan Greenway for the copyright research. ... '
Communicating results • O~HOI" I'A ILll '"" r1
PRAT872 - 0621 -22807 WORLD-
The res.ulLS oi tes!ing a scientific theory are published- scientis-ls need to
'"
let others kno\v about their work. ScienLists publish their results in scientific F. ,,_ .......~ .....
Clipart from Core!• journals. These arc just like normal magazines, only they contain sciemific
reports (called papers) that use scientific terminology, instead of the latest
Text, design, layout and original illustrations e Coordination Group l'ublications Ltd. (CGl'l 2020 celebrity gossip.
Rgure 1: 11te first
All rights reserved. Scienlific rcporis are similar to Lhc lab write-ups you do in school. British sdcntific journal,
And just as a lab wrilc-up is reviewed {marked} by your teacher, repons in 'Philosophical Transactions
scientific journals undergo peer review before they're published. The repon is of rile Royal Society;
sent out to peers - other scientists who are t'..xpens in the same area. publi51H!d in 1665.
08001712 712 • WWW.C!J>boolcs.co.uk
How Science Works
The other scienlists go through it bit by bit, examining lhe methods
Tip: Scientific rcsea.rdl and data, and checking i~s all clear and logical. Thorough evaluation allows Example------------~
is often funded by The structure of the al·om
decisions to be made aboul what makes a good methodology or experimental
c:ompanic.-s wflo have
technique. Individual scientists may have their own elhical codes (basc.->d It took years and years for the current model of the atom to be developed
a: vested interest in iis
OUIComes. Scicmists I on their humanistic, moral and religious beliefs), bul having their work and accepted. moj
are ethically obliged 10 scrutinised by other scientists helps to reduce the effect of personal bias (either Dalton's theory in lhc early 1800s, that aloms were solid spheres, was
1113f<e sure that this doos deliberate or accidental) on the conclusions drawn from the results. disputed by the results of Thomson's experiments at the end of that century. Tip: See p.41 I for
~s their rcsuhs. When the report is approved, it's published. This makc'S sure that As a result. Thomson developed the 'plum pudding' model of the atom, on the clcwlopmem ol
work published in scientific journals is or a good standard. But peer review which was later proven wrong by Rutherford's alpha-scattering experiments the model of the atom.
can't guarantee the science is correct - other scientists still need to reproduce in the early 1900s. Rutherford's 'nuclear model' has since been developed
it. Sometimes mistakes are made and bad work is published. Peer review and modified further to create the currently accepted model of the atom we
isn't perfect but itS probably lhe besl \Vay (or scientists lo self-regulate their use today- but scientists are still searching (or n1ore accurate models.
work and 10 publish quality reporlS.
Validating theories Collecting evidence
Other scien1ists read Lhe published theories and results, and try lo test the 1. Evidence from lab experiments
theory themselves in order to validate it (back it up). This involves:
Results from controlled experimenls in laboratories are great. A lab is the Tip: Pages 23-29 aro
Repeating the exact same experiments. easiest place to control variables so thal they're all kept constant (except all about carrying out
Using the theory to make new predictions and then resting them with neo.v for lhe one you're inves1igating). This means you can draw meaningful practicals..
experiments. conclusions.
Examples Example
Tip: Once an
e:xperimcmal method In 1989, two scientists claimed that they'd produced 'cold fusion' (the The pressure of a gas
energy source of the Sun but \vithout the high temperatures). If iL was
is found 10 give good I( you're investigating how the volume of a gas affects its pressure, you
evidence i1 beromes a true, it would have meant cheap energy for the world forever. However, need to keep all other factors constant. This means controlling things like
p,aj!llgll - an accepted other scientists juSl couldn't reproduce the resullS, so the theory of 'cold the temperature or the gas. Otherwise there's no way of knowing that the
nwthod to 1es1 that fusion' couldn't be validated. [
panicular thing th.a1a ll volume change is what is causing the pressure to change.
In the 1960s it was proposed that panicles like protons were made up
scicmi sts can use.
of smaller panicles called quarlcs - the quarlc model (p.424). After
2. Investigations outside the lab
this, many experiments were conducted Lhat supported this idea, and so
validated the quark model. There are things you can't study in a lab. And outside the lab, controlling the
variables is tricky, if not impossible.
Example
How do theories evolve?
Does living near power lines increase the risk of
If multiple cxperimenLS show a theory to be incorrect then scien1ists eilher developing certain cancers?
have co modify the 1hcory or develop a ne\v one, and start the testing again.
You could c.'Ompare the number of cancer cases in a group of people who
Tip: Sometimes data If all the experiments in all the world provide good evidence to back a theory live near power Jines to a group of people who don'l. But there are ahvays
cfraonm b oen Leh ee xsptaenriimnge m Bupu,t tiht ew tihlle noervy eirs btheocuogmhet otoft aasll ysc iinednitsifpiuc ta'fbalcet' f(afcotr. nSocwie) n-tifisce bcr Feiagkutrher o2u. ghs dwiefflel-rdeensciegsn bede1 swtuedeyn ugsrionugp ms oaft dpleeodp lger.o uTphse -becsth yooous ec atwn od gor oisu 1p0s h oafv pee ao ple
poinl for developing a or advances could provide new ways to question and test lhe theory, (those who live near power lines and those who don'I.) that arc as similar as
ncwthoory. which could lead to new evidence that connicts with the current evidence.
possible (same mix or ages, same mix of diets etc.). But yoo still can'I rule
Then the testing s1ans all over again ... And this, my friend, is the tentative Rgure 3: Studies are
nalure of scientific knowledge - it's always changing and evolving. oul every possibility. ongoing to determine ii there
is a link bef\.\1?en proximity
rr;::;;-J to power lines and the risk of
Cothmem reusnuilctas1 e _., Valtihdeaotery th e 1-E~v;de-n~.c e+!~ cancer.
Science and decision making
supports
;r Scientific knowledge is used by society (that's you, me and everyone else}
Evidence di.'ipf<M':S it Lo make decisions - about I.he way we live, whaLw e eal, what we drive,
Rgure 2: Flow diagram summarising the sciemific proces.s. etc. All sections of society use scientific evidence 10 make decisions, e.g.
politicians use il 10 devise policies and individuals use science to make
decisions about lheir own lives.
•E"•I
How Science Works How Science Works A
Example-------------
Tip: llon'1 gco mixed up Module 1
- it's not lhc scicmiscs X-rays are used in dentist!)' to see images of lhe Leeth inside the human
who make the dedsions,. body. They're used 10 monilor denial heallh, including s<!eing when adulL
il's society. SciemiS1S leeth or wisdom teeth are coming lhrough.
just produce evidence
to help society make Lhc Hinocwreeavseerd, sricsike nocfe c ahnacs efro. uTnod ma ilninimk ibsee ttwhiese rnis ekx, pthoesruer ea troe rXe-srtaryicst iaonnds on 1. Planning an Experiment Leaming Objectives:
decisions.
when X-ray images of a patient's mouth can be taken (e.g. not during
pregnancy}, and how often. As a result, patients don't tend to have X-ray You have ro do practical 1.vork in class as pan of your course. You~IJ be asked • dKensoigwn l \eOxp\ve :lrOim cms,
images laken as part of their standard check-ups, unless there is a strong ;:ibouc it in exams too, so you nec."Cl to knavv how to plan lhe perfect experiment. including how to
medical reason to do so. solve problems set in
l @""". a practical con1ruct.
Designing an experiment ~11]
@ • Be ablo 10 identify
Before you srart planning an experimen~ you need - variables Lhat must
Factors affecting decision making Lo be clear about what you're 1rying to find out. You mighL be asked be controlled, where
Lo design a physics experiment to investigate something or answer appropria1e.
Tothfie pryi:s mkP aaoklosepo l deae'sfcf episcetirsoc nhosop. twio o sTuhde ls acise pnetirfsico neavli dbeiansc aen wde b healiveefs c, apnu bbleic o ovperinshioand,o awnedd t bhye omthederia i.n fluences sao qmueelshtiionng .a php clioeudl,d libkee ad elaebid eixngp ewrihmicehn lb tuhialdt iynogu m'vea tseereianl bise b{oerse! ,f oorr a • aBpep arbolper itaote s eulneictts for
For example, people Economic factors particular job. Either way, you'll be able 10 use the physics you know measurements.
may underestimate Lhc from your course and the skills in this topic to figure out the best way to • Know how 10 use
risk of things with Society has to consider the cost of implementing dlanges based on scientific in11CS1iga1e the problem. a wide range of
long-1erm harmful conclusions. Sometimes it decides the cost outweighs the benefilS. practical apparatus
eimffomceisd tihaatet layr seene'tn . Example Planning experiments caondrr etectclhy.n iques
Building new po\ver plants thal use renewable energy resources helps
Planning an experiment properly helps to make your resullS valid, • Be able to evaluate
Tip: economic factoo Soo mreedtuimcee so uthre c con~tr iobfu b1iuoinld tion ggl ao bnaelw w palramnitn igs bjuustt itto coo mstsu cmho fnoery t.h e apcacguesra, lbeu at nhde rper'se cai sseu m(semea pry.1 o8f} .h Tohwe ryeo'su pgloe natbyo ou{t iint.f.o. on the next few ewxhpeethrfi'm..re annta l method
just mean anything 10 [ government to justify it, especially when government money could be is appropriate to
do with money, and put to more immediate use in, for example, the NHS Of schools. Make a prediction Of hypothesis - you need to come up with an meet 1heexpcaoo
social raaors ju~1 mean idea (or quescion) based on a 1heory. This is what you'll be trying OUIC0111ClS.
anything 10 do with to prove (or aoS\ver) wilh an experiment. Specification
people. Social factors Think about the aims of the experiment and identify the References 1.1.1
Decisions affect people's lives - sometimes people don't want to {ollow independent, dependenl and control variables (see below). and 1.1.2
advice, or are slrongly against some recommendations.
Select appropriate equipmenl (see page 7) that
Examples will give you accurate and precise result.Ii.
Exposure 10 UV radiation from tanning beds can lead to cancer. Do a risk assessment and plan any safely precautions (sec pages 8, 24 Tip: There's loo more
Scientists recommend that people don't use tanning beds, but shouldn't and 25). aboul how hypoohescs
are created and the
we be able to choose whether we \Vant to use them or not? Decide whal data 10 collect and how you'll do ii (p.9). scientific process in
People may no1 want new wind farms to be buih in certain locations, Write out a dear and detailed melhod - it should be clear enough How Science \"larks on
as they believe that the turbines spoil the view. that anyone could follow it and repeat your experiment exactly. pages1-4.
Carry out tests - to provide evidence that will
Environmental factors suppon the prediction or refute il.
Some scientific research and breakthroughs might affect the environment.
Not everyone thinks the benefits are wonh Lhe possible environmental damage. Variables
Rgure 4: ~Vind f'a°r ms arc Example-- You probably know this all off by heart but il's easy 10 gel mixed up
often built at sea reduce Hydroelectricity requires the building of a danl. This often destroys the sometimes. So here's a quick recap.
rite impact on people. habitats of plants and animals, so many think that other renewable energy A variable is a quantity that has the potential to change, e.g. mass.
resources should be used instead. There are two types or variable commonly referred to in experiments:
Tip: Time is alwavs an
indcpcndem variable.
Independent variable - the thing lhat you change in an experinlcnL
Dependent variable - the thing that you measure in an experiment.
+ .+
HowScienceWorks Module 1 Development of Practical Skills
Example----------- Think about the range you plan on taking measuremenlS over too
- e.g. if you're measuring the effect of increasing the force on a spring. you
You could investigate the effect of var)'ing the po1ential difference across a need to know whether you should increase the rorce in steps of 1 newton,
filament lamp on the current nowing through it using the circuit shown in 10 newtons or 100 newtons. Sometimes, you'll be able to estimate what
Figure 1 below:
effect changing your independent variable will have, or sometimes a pilot
experiment migh1 help. In a pil<>' experiment. the apparatus is set up as ii will
Tip: For more on J tfhuete pn1oitoemnteiatel rd iF-TCtole naclete i Po.vet supply. be used in the actual experimcnl. and lhe independenl variable is varied 10
potemiometers see supplied ro the filament see (roughly) how much the dependent variable changes.
page 180. lamp fr00> O V"' the
source voltage, V. -
Example------
Voltmeter - to measure A student is investigating the extension of a tesLw ire using the apparatus Tip: There's more on
the potential differCfftCe. in Figure 3. She \Viii add weights to the wire and measure ilS extension upasgineg tt2hi4s. a pparatus on
Rgure 1: Grcuil diagram for measuring the current flowing J.hrough a filament lamp. using 1he marker and the ruler.
The independent variable will be the potential difference supplied to Tip: The ex1ension
the lamp. being measured here
is very small, so you
The dependent variable will be the current flowing through the lamp. need a long piece al
wire for the change to
be noticeable. The wire
Apart from the independent and dependent variables, all other is too long to suspend
variables should stay the same during your experiment These are knovv"n as vcnically from a clamp,
control variables. If control variables are not kepi the same, you can't tell V.'t.>ig/JLo; which is why the pulley
whe1her or not lhe independent variable is responsible for any changes in Rgure J: Experimental set-up for invesligating the exmnsion of a test wire. is more suitable her<!.
your dependent variable, so your results won't be valid (page 18). Control
variables that are likely to change during your experiment should be measured She decides to do a pilot experimenl 10 decide on the incremenls in which
she should add wcighlS to the tesl wire. She is aiming to find out how Tip: Measuring a
to ched: that they are conslant throughout the experiment. much weighL needs lo be added to cause the marker on the wire to move a distance Lhat is small
measurnble distance along 1he ruler that can be clearly recorded, bul 11~m't compared to the
Example cont. bring the wire close to Lhc poinl al which it will snap. resolulion of your
So for the circuil experiment above, the con1rol variables include the length equipment will lead to a
high percentage error in
Figure 2: The filament in a of the connecling leads1 the filament bulb used and the lemperature of your measurements -
bulb is designed "'lleiit up, the circuil wires. To keep lhe lemperature coostanL, you might use small Considering your measurements before you start will also help you see page 1&.
cmsoo.ao iklte isn thh boeeu etlwdx pebeeern iam rlkeepMnet1 eaatd sf attoior [ dpuortienngti athl ed eifxfepreernimceesn (ta,n adn dc uarlrleon\vts }l htoe sfitloapm ethnet ctoir ccuoiot l\ Vbiertews eheena lrienpge uapts . cYhoouo wsea nLth e10 mpoicskt athpep raopppraiartaet uasp tphaarta twuisl l agnidve l t.)'C'OhUn ithqeu ebse fsot rr ethsuel leSx. pMeriamkee nstu re
you know how to use all the instrunlents and equipment you've come across
lP.St. in class and can carry oul all the lochniques too.
Examples
Apparatus and techniques
If you're measuring the length of a spring that you're applying a force
Before you stan, make sure you're measuring things using appropriate to, you mighl need a ruler. If you're measuring the diameter of a \Vire, Tip: Rcmember-
units. To choose the correct units, you need to Lhink aboul what scale your you'd be beucr off with some t:;illiper.;. pan o/ choosing your
measurements of 1he independent and dependent variables are likely to be If you're measuring a time inlerval, you could use a stopw.ndl. If fhe apparaLus and planning
on (e.g. millimetres or metres, milliseconds or hours) and how you're going to time is really short (for example if you're investigating accelera1ion due yinovuorl vteec thhniniqkuineg w aibllo ut
analyse the results later. to gravity of an object as it falls to the Roor), you might need something safety precautions. This
n1ore sensitive, like light gates (see page 66). should all be covered in
Example your risk a:sscssmcru (see
If you're measuring time, ii might be beuer 10 use seconds rather than pages 8, 24 and 251.
minu1es - when you come to processing your results, i1'1l be easier 10 Make sure you perform al I techniques carefully and that any
work with a result of 73 seconds than a result of 1.217 minutes. apparatus is set up correctly- this will help lo minimise errors whidl \vould
affect your results. E.g. if you're measuring a lenglh, make sure your eye is
level with lhe ruler when you take the measurement.
MW Module 1 Development of Practical Skills Module 1 Development of Practical Skills
Identifying risks 2. Recording and Processing Data
~
Learning Objectives:
You'll be expecled 10 show that you can identify any risks and ~ • Be abl11 to record and
hazards in an experiment You'll need to take appropriate safely Time lo find out haw lo record your dala correctl't and h<MI 10 do n1.1ths-y present observations
measures depending on the experiment. For example, for anything things wirh your data like calculating means. The fun doesn't end. .. and data in an
involving lasers you'll probably need 10 wear special laser goggles. appropria1e format.
Tables of data
• Understand 1he terms
Evaluating experiment designs @--~~ You need to make a table to write your res.ullS in. You should include: 'qualitative results'
If you need 10 evalualc an experin1en1d esign, whether it's your own ~ Space for your independent variable and your dependenl variable. arensdu l'lSq'u.a ntitalive
Rgure 4: Goggles should or someone else's, ~·ou need to think about the follo\ving things: You should specify the units in lhe headers, not within the rable itself. • Beable:tousc
be used in most experiments Does the experiment a<.iually 1-est what it sets out to test? Space to repea1 each measuremenl a1 least three 1imes to reduce random significant figures
lom par.otintega o toh;ee rCu)f,! Ss nfraopmpi nJJgJ Y Is the me(hod clear enough for someone else to follow? error and make sure your final resuhs are more precise (see p. 17), and lO appropriately.
wires, dredmaniCg.eJlNs .a nd olhet Apart from the independenl and dependent variables, Ssppoatc aen foomr aanlyo urse sruelstus hfsro (mp. 1dO aJi.a processing you need to do, e.g. calculating • eBxep aebrilmQ etom parlo rceessuslt s.
is everything else going to be properly controlled?
the mean from repeats (see lhe next page), or calculating speed from • Be able: to USC
Are the apparatus and techniques appropriate for wha1's measurements of distance and time. {Your table shouldn't include your appropriaie
Exam Tip being measured? Will lhey be used correctly? workings, jus1 the results from your calculations.) mathematical skills to
gEimextaptmirnogivn eeymrosu eJ ntootvs e st uo~ est Wto iblle t htaek mene tihn oodr dgeivr eto p rceaclcisuel aretes ual tms?e aEn.g v. aalruee r(espeeea pt amgeea 1s7u)r?e ments going and the dYeopuern tdabenlet vsahroiaulbdle h ainv eth teh ec oilnudmepnes nndeexntt t ov atrhiaabt.l eA inny t hrees fuilrtssi fcroolmum dant, a dparotac.e ss quan1itative
am me1ehtohdosd - coou.lgd. bhoow ls lhe experiment going to be conduc1ed safely? oprfo tcaebsles inygo us hmoiuglhdl bened in u tph ew fiulhrt hwehset nri gyhotu-h iannvcds tciogalu1em Lnh(se) .e ffFeigctu oref 1p oitse tnhteia slo rt • aeBxoepo aembrialmeJi eetosn tiiandle ntify
improved to make the difference (p.d.) on current.
resuhs more precise, so mcas.u.rements.
make sure you know Current I A Current/ A Current/ A Mean current Specification
how to design a good Q1 A studenl is investigaling how lhe angle of a ramp, 8, affects lhe final l'.d./V Run 1 Run 2 Run 3 I A (to 3 s.f.J References 1.1.2
experiment velocity of a trolley as it Lravels 1 m down I.he ramp. He measures 1.1.3and 1.1.4
0.0 0.000 0.000 0.000 0.000
1he velocity at the bouom of the ramp using a Jighl gate. The s<udent
assumes the friction ading on the trolley is negligible. He sets up the 1.0 0.104 0.105 0.102 0.104
following apparatus: 2.0 0.150 0.151 0.149 0.150 Tip: You should
give all ofyourdala
3.0 0.188 0.187 0.187 0.187
to the number of
4.0 0.219 0.220 0.193 0.220 decimal places that
Tisi ap: s uTihtaeb llieg hpti egc;i1e0 o f Figure 1: Table of results showing the effect ofp .d. on curront through a resiswr. -youe .mg.e oa.souoroe dA .10 n o1
apparatus 10 use in Most of the time, you'll be recording numerical values, known as justOA
1his experiment as quanlitath»e data. Occasionally, you may have to deal with data that can
it can measure the be observed but not measured with a numerical value. This is known as
instantaneous velocity
qualitative d,1ta (see Figure 2). It's still best to record lhis kind of dara in a
ohhc trollQy as it is
table to keep your results organised, bul the layout may be a liule different.
accelerating. This i:s a) Name Lhe independent and dependent variables in this
not possible with a
stopwatch. investigation. Rounding to significant figures
b) Name one variable in this investigation that the student should When using your data in further calculations you need 10 consider significant
keep lhe same. figures. The first significanLf igure of a number is the first digit 1hat isn't a zero.
The second, third and fourth significant figures follo\v on immediately after the Figure 1: Measuring
I iMl:t:i!P.111 first (even if they're zeros). how the diffracUon of
frtNH3:1.-llt~fJU.l.Q water waves varies with
Ql Why is it important to make sure the conlrol variables don't change Exan1ple -i.•.tji$"1fhd gap width will in'o'O/Ve
during an experiment? 0.6074976 rounds to 0.61 to 2 s.f. and 10 0.607 to 3 s.f. recording qualitative data.
Q2 State what is mcan1 by a pilot experiment, and explain why
When you're doing calculations using measurements given to a
lhey are used.
certain number of significant figures, you should gfve your anS\ver to the
QJ Give Lhrce things that must be considered when evaluating an lowest number of significanl figures that was used in the calculation.
experimental method.
The lov.. • est number of signfficanl figures in the calculalion is used
because the fewer digits a measurement has, the less accurate it is. Your answer
can only be as accurate as the least accurate measuremenl in Lhe calculation.
* ·
M :M Module 1 Developmenl of Praclical Skills Module 1 Development of Practical Skills M
Example -ft§!$1§1N 3. Presenting Results
Exam Tip 1 Leaming Objective:
You shouldn't give Forthe calculation: 1.2 ~ 1.85 = 0.648648648. .. • Be able 10 plot
your answer to too few 1.2 is given to 2 sJ. and 1.85 is given to 3 s.f., so the answer should be When ymlre planning an experiment, you nt.>ed to think about the bes.t way lo suilab1e graphs from
sifi g1hncif ikcMan·et sf1ign uurmesb. eSr o given to 2 s.f.: 1.2 ~ 1.85 = 0.65 (to 2 s.f.) present your results. It all depends on ~vhat son of daLa you've gor ... einxdpuerdiminegn steall ercetsinulgts ,
of significant figures Types of data and labelling ax<?S wilh
itnh ean c)a'OlUcu slhaotioolnd ins' t3 g, ive Calculating a mean 1. Discrete data aqpuparnotiptriieas1 acn sdca ulensi,t s.
your allSIA•er to I ex 2 For many experiments, you'll need to calculate the Yoo gel discrete data by counting. E.g. the number of weights added 10 che Specification
significant figures. You arilhmetic mean (average) or some repeated measurements: end of a sp<ing would he discrece (see Figure 1). You can't have 1.25 weights. Reference 1.1.3
could lose a mark in 1hc
That'd be dafc. Shoe size is anolher good example of a discrete variable -
exam if you do this. arilhmelic mean (average) sum or your repeated measuremenss only certain values are allowed.
of a measurement number of measuremenls taken There are lots of ways to present discrete data, depending on what
other data sets you've recorded. Scalier graphs (p.12) and bar charts are often
Walch out for anomalous results. These are ones that don't fit in
Tip: Just bocausc )'00 wich the other values and are likely 10 be wrong. They're usually due 10 used.
ignore anomalous results
experimental errors, such as making a mistake when measuring (see page 36).
in your calculations, you 2. Continuous data
shouldn't ignore them You should ignore anomalous results when you calculale averages. A continuous variable can have any value on a scale. For example. ~ ~~
in your write-up. Try Example -f1t@S1fl1!j Lhe extension of a spring or the current through a circuit. You can
to find an explanation never measure the e.xacl value or a continuous variable.
for what wem wrong so Look al lhe cable in Figure 1 again - lhe currenl al 4.0V in Run 3 looks
that it can be avoided in Ii ke it mighl be an anomalous result. It's much lower Lhan the values in The best way to display t\vo sets of continuous data is a line graph or a
future experimems. the other lwo runs. II could have been caused by the filament lamp being scalier graph (see page 12). I
hotter at the end oi Run 3 than it was al the end of the first two runs. I
The anomalous res.uh should be ignored to calculale lhe average: 3. Categoric data ~I
A categoric variable has values thal can be sorted into categories.
With anomalous result (0.219 + 0.220 + 0.193) ~ J = 0.211 (lo 3 s.f.) For example, types or malerial might be brass, wood, glass or steel. :n
Wi1hou1 anomalous result (0.219 + 0.220) ~ 2 = 0.220 (lo 3 s.f.) If one of your data sets is categoric, a pie chart or a bar chart is often 'I I
So chc average currenl al 4.0 V should be 0.220 A (ra1her1han 0211 A). used 10 present 1he dara - see Figure 2. Rgure 1: 111e number of
l"l'eights added to a spring ;s
discre1e data. The spring"s
'®"4:1.-lll:Q;t.},pQ.fffll@tjiftjjj wind etM'Jb'Y 3% cxten.sion is conHnuous data.
othE-~r 2%
Ql Calculate lhe following, giving your answer 10 the correct number or
significanl figures:
a) 4.53 x3.142 b) 0.315~0.025 />timing c:oal
Q2 A scienlist carries out an investiga1ion to find lhe force constant of 45%
Tip: There's more on a spring. She adds differen1 masses to the spring, then records the
this spring experiment weight of the masses and the spring's extension. Her results are Number (If p:mides
on page 116. shown in che table below. Complele the cable by calculating lhe burning natural (oon-li11e.:u J<'Ale)
ga.~·25%
mean extension or the spring for each weight.
Exrension I cm
Weight IN
Trial 1 Trial Z Trial 3 Mean
Rgure 2: caiegoric data of diffe1ent types of e1'/lefgy
z.o Z.9 .J.2 .J.I p1<xiucrion in a particular couniry p!e5P.11ted on a pie cha1L
4.0 5.8 8.6 5.9
6.0 8.4 8.4 8.5 4. Ordered (ordinal) data
Scauenng "'Jfea on p.lflkks
Ordered data is similar to C'..ategoric, bul 1hc categories can be pul in order.
aimed al gold Jheel
For example, if you classify frequencies of light as 'low', 'fairly high' and
Figure 3: Ordered daw of
'very high' you'd have ordered data.
particle scattt.ving efifxts
Ql Whal is meant by quantitative daca? A bar chart is orLen used if one of your data sets is ordered - see Figure 3. presented on a ba1 chart.
Q2 Whal is an anomalous resuh?
!18 Module 1 Development of Practical Skills Module 1 Development of Practical Skills Ml
Scatter graphs 4. Analysing Results
Tip: Axes incremems Learning Objectives:
should go up in sensibla You can plot discrete or continuous data on a scalier graph. These are • Be abl11 to analyse and
amounts thal arc easy useful for spotting any correlation between lwo variables (see the next page). Now you've got your data, you can use your results lO describe what happened in1erpret qualitative
plot, like ls, 2s, 0.1s, Usually, the independent variable goes on the x-axis an<l the dependent in the experiment You can also use your results to calculate n10rc quanriLies. and quamhativc
etc. You shouldn't e\'er variable goes on lhe y-axis. Both axes should be labelled dearly, with the experimcmaJ results.
uliskee a3ws okwr alrsd a sin acnreym ents quantity and unilS. The scales used should be sensible (i.e. they should go Qualitative data • Be abl11 to use
imcrmediate points up in sensible steps, and should spr~.ad the data out over the full graph rather Analysing qualitative dala is a bit more wordy than analysing quanlitative appropriate
between those labels than bunching it up in a corner). If you need to use your graph to measure data. You need to be able to lalk about what your resullS are showing. mathematical skills
wploout lodr breea vde.r y tricky 10 smoemaesuthriinngg, lshecl egcrat duineintsl foorr t yhoe uirn atexrecse ptht,a st ewei lpl algeet sy o1u4 dano dth 1is5 )e.a sily (e.g. by Example----------- qfoura anntiatlaytsivise odfa ta.
Plot your points using a sharp pencil, to make sure they're as accurate An experimenl is carried out to see the diffraction patterns produced • Be able to interpret
as possible. You need to draw a line of best fit for your resuhs. Around half by shining a laser through a slit in a piece of card. The size of the slit suitable graphs
the data points should be above the line, and half should be below it (you is varied to see the effect on the diffraction pattern. from experimental
sTuirpe: tYhoeo s cshaloeu ilsd lmabaekl•le d should ignore anomalous resuhs). Depending on the data, Lhe line of best fit A sketch of the results are shown below. traeksuinltgs ,m inedasuudrjenmg ebnyt s
with numbers regularly, might be straight or curved. Slit =0.02 mm Slit = 0.04 mm Slit= 0.06 mm of gradients and
ela.grg. ea st qleuaasrte esv. ery three Example --1$§!$"$11 I I II II 1111 I Ill intercepts.
Specification
An experimenl is carried out to see how the acceleration of a trolley is
Reference 1.1.3
dependent on the force-acting on iL The results are sho\vn in the graph.
From these results you can see thal as the slit gets wider, the paltem
The force is lhe geL'i narrower - there are more fringes in a given area.
independent variable
and so is on the x-axis.
The acceleration is the Scatter graphs and correlation
dependent variable and
so is on the y-axis. Correla.tion describes the relationship bct\vecn two variables
- usually the independent one and the dependent one. Data can show
The line of best fit is
positive correlation, negative correlation or no correlation (see Figure 2).
a straight line, wilh Figure 1: The diffraction
fo1t:e IN 2 points above the line Positive correlation Negative correlation No correlalton pattern p1rxfuced when a
and 2 points below iL As one variable As one variable There is no laser is shone through a slh.
increases, the other increases, the other relationship between rhe.re~ mote on diffraction
Exan1ple -l8§!!j1§i8 also increases. decreases. the variables. pauerns on p.212.
In the graph on the f' .. . . .. Tip: You have to be very
right, the points show
careful wflen drawing
that the velocity conclusions from data
is increasing at an ~ like this because a
increasing rale over lime. correlation becwcen two
So a curved line or variables doesn'La lways
besl fit is drawn. Rgure 2: Sc.met g1aphs sha.ving positM!, negative and no correlation. mean that a dlange in
lime Is ona variable ea uses a
Linear graphs change in the other.
Practice Question - Application lnere's more on this on
If you plol two variables thal have a linear relationship, you'll get a pagc20.
Ql A car is accelerating along a road. A computer connected to the car straighl line or beSl fit. The equation of a straight Ii ne is y =nix + c, where
measures the velocity oi the car every 2.S s. The results are shown in m =gradient (slope of the line) and c = y-interccpl. This means you can use
the table below. Plot a suitable graph for the data. your graph lo work out certain values, and the relationship between your
variables.
Time/s 0.0 2.5 5.0 7.5 10.0 12.5 15.0
Ve/ociLy I mph 0.0 12.8 21.4 29.0 33.3 35.8 37.0 Proportionality
If you plot l\vo variables against eadl other and get a straight line Lhal
goes through the origin, lhe two variables are directly proportional. The
Practice Questions - Fact Recall y-intercepl, c, is o. so the equation of the straight line is y = mx where m is a
Ql Give one way that categoric dala can be presented in resulls. constant The con:S!anl of proportionality, m, is the gradienl or the graph.
Q2 Which variable usually goes on the x-axis of a scatter graph? You can show 1wo variables as being diredly proportional using the
symbol a. For example K tx y means tha1 x is directly proporlional Loy.
eA
•llf~-· Module 1 Development of Practical Skills Module 1 Development of Practical Skills •
