Exemplar IB Science Internal Assessment
This is a mock internal assessment designed to show you what to include in a good IA, how to write and how to present it. Whilst the
experiment itself is not realistic, the way it is treated is, and the exact same methodologies apply to a chemistry, biology or physics
investigation.
Research Question:
What is the time-dependent effect of Justin Bieber on the quality of a person’s music collection?
Independent Variable:
The number of Justin Bieber songs in an individual’s iTunes library.
Dependent variable:
The change in quality of the music collection - determined by the average score achieved on Metacritic by the album
to which each song belongs – over the course of one year following contamination of the collection with the music of
The Bieber.
Controlled Variables:





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Age – musical taste is strongly related to age, decreasing steadily from birth until age 18 and improving
dramatically until age 32 at which point it levels off. This experiment will look only at the musical taste of 18
year olds.
Gender – it is well known that boys have better musical taste than girls. However, as most boys suffer from
Bieberphobia and thus have little to no Bieber in their collections, the experiment will look at the musical
taste of girls.
Nationality – of all nationalities it is widely accepted that the English have the best musical taste; as such the
effects of Bieberism should be most pronounced and thus easiest to measure with English people.
IQ – the effects of IQ on musical taste are not well known but to avoid any potential difficulties, a sample of
individuals with average IQ (95-105) will be used.
Wealth – similar to IQ, the effect of wealth on musical taste is not well understood so the sample will
contain individuals with the median family income for the UK.
iTunes Container – the vessel used to contain an iTunes library makes a big difference. Those choosing a
non-Apple device such as an Android phone tend to have more sophisticated but less cool taste than those
who use standard Apple devices. To control this variable we will use iTunes libraries that are contained in
standard Apple iPods.
Size of iTunes library – it is expected that the Bieber effect will be comparatively greater with smaller iTunes
libraries, thus a standard library size of 1000 songs will be chosen.
Apparatus:
 18 iTunes libraries meeting the following criteria:
o They belong to an 18 year old English female of average IQ and income
o No prior Bieber contamination
o Stored in standard Apple iPod
o Contains exactly 1000 songs
 The entire Justin Bieber music catalogue
 Standard laboratory Bieberometer with Metacritic probe (accurate to +/- 0.05%)
 250 ml beaker
 Stirring rod
 Calendar (accurate to +/- 0.5 days)
Method:
1. Take one iTunes library, pour into a 250 ml beaker and use the Bieberometer to measure the music quality
to 1 decimal place.
2. Contaminate the iTunes library with varying amounts of Bieber, according to Table 1 and mix thoroughly. For
each Bieber song chosen, a randomly selected song from the album should be removed in order to keep the
total number of songs constant.
3. Pour the library from the beaker, back into the iPod.
4. Return the iPod to its owner, wait 3.00 years and re-measure the music quality using the Bieberometer
5. Repeat steps 1-4 a further two times.
Table 1: Quantity of Bieber to be Added
Experiment Number
1 (the control)
2
3
4
5
6
Diagram:
Amount of Bieber Added
(songs)
0
5
10
15
20
25
Observations: Table 2 - Quantitative and Qualitative Data
Analysis
Calculation of change in music quality:
This was simply the difference between the initial and final music quality for example, using the data for Experiment
1, Run 1:
Change in Music Quality
= Final Music Quality – Initial Music Quality
= 70.1 - 50.1
= 20.0%
Calculation of average change in music quality:
A simple average was used which using the data from Experiment 1, Run 1 would be:
Average change in music quality
= (Sum of Change in Music Quality) / Number of Runs
= (20.0 + 19.4 + 18.1)/3
= +19.2%
It should be noted that the results for Experiment 4 Run 1 have been disregarded and the calculations adjusted
accordingly as it is clearly anomalous when compared both to the results for Runs 2 and 3 of Experiment 4 and for
Run 1 of the other experiments.
Calculation of rate of change in music quality:
This was the average change in music quality divided by the length of the experiment in years, which using the data
for Experiment 1 is:
Rate of Change in Music Quality = Average Change in Quality / 3.00
= 19.2 / 3.00
= +6.4 % per year
Calculation of Uncertainties:
The relative uncertainty in the final results was calculated by adding the percentage uncertainty of the music quality
measurements to the % uncertainty in the measurement of time. Using the data for Experiment 1 this is as follows:
Relative uncertainty
= % uncertainty of quality measurement
= (uncertainty of Bieberometer x 2) x 100
Change in music quality
=( (0.05*2)/6.4) x 100
= +/- 0.66%
+ % uncertainty of time measurement
+
uncertainty of calendar x 100
length of experiment
+ ( (0.5 x 3)/(365 x 3)) x 100
The absolute uncertainty was the % uncertainty multiplied by the calculated rate of change of music quality. Again
using the data for Experiment 1 this was:
Absolute uncertainty
= Relative uncertainty x Rate of Change of Music Quality
= 0.66 x 6.4
= +/- 0.04 Metacritic % per year.
Please note, all calculations were carried out using an Excel spreadsheet and are summarised in the following tables
2 and 3
Table 3: Processed Data
Run 1
Run 2
Run 3
Average
Experiment
Number
Amount of
Bieber Added
(songs)
Change in
Music Quality
(Metacritic %,
+/- 0.10)
Change in
Music Quality
(Metacritic %,
+/- 0.10)
Change in
Music Quality
(Metacritic %,
+/- 0.10)
Change in
Music Quality
(Metacritic %,
+/- 0.10)
1
0
20.0
19.4
18.1
2
5
9.2
11.8
3
10
-0.1
4
15
5
6
Rate of Music
Quality Change
(Metacritic %
per year)
%
Uncertainty
Absolute
Uncertainty
(Metacritic
% per Year)
19.2
6.4
+/- 0.66
+/- 0.04
9.6
10.2
3.4
+/- 1.12
+/- 0.04
1.0
0.0
0.3
0.1
+/- 33.47
+/- 0.03
-31.9
-10.0
-9.4
-9.7
-3.2
+/- 0.89
+/- 0.03
20
-19.7
-18.2
-20.0
-19.3
-6.4
+/- 0.38
+/- 0.02
25
-29.9
-29.0
-30.8
-29.9
-10.0
+/- 0.2
+/- 0.02
Graph 1: Processed data graphed using Microsoft Excel.
Change in Music Collection Quality (Metacritic % per year)
Music Collection Quality Change vs Number of Bieber
Songs
8.0
6.0
4.0
2.0
0.0
0
5
10
15
20
25
30
-2.0
-4.0
-6.0
-8.0
y = -0.6549x + 6.5624
R² = 0.9995
-10.0
-12.0
Number of Bieber Songs in iTunes Library
Please note that this graph does include error bars, however, they are too small for Excel to be able to display.
Conclusion
The data shows a strong, inverse, linear relationship with the quality of teenage English girls’ music collections
decreasing as the number of Bieber songs increases. The data suggest that every additional Bieber song correlates
with a 0.65% per year reduction in the quality of an individual’s musical taste. It is worth noting that 10 Bieber songs
in a collection represents a critical point where the Bieber effect more than offsets the increase in taste associated
with aging and leads to permanent declines in musical taste. The results of this study are broadly similar to those in
the research literature with Lopez et al recording a 0.55% per year decline and Midgeley et al recording a 0.80% per
year decline. However both these groups used a different methodology and so it is difficult to draw direct
comparisons.
The results can be explained largely due to the Bieber effect. It is well known that Justin Bieber and his music emit a
form of radiation that inhibits the areas of the brain responsible for rational thought and decision making. This leads
to affected individuals making terrible decisions when downloading and buying music resulting in the observed
decreases in musical quality, and eventually the death of their souls.
Evaluation
With the exception of the aforementioned anomaly (Experiment 4, Run 1) the data collected appear to be highly
reliable with the different runs of the same experiment being highly consistent and the very high R2 value of the line
of best fit showing that separate experiments agree strongly with each other. The relative and absolute errors in the
data are very low and the data broadly agree with the literature findings and so it can be said that the data is reliable
and the experimental method was sound. It is worth noting that the % error for experiment 3 was very large, this is a
result of the overall change in music quality being very small and so it is important here to focus on the absolute
error which remains very small. The anomalous value for Experiment 4 Run 1 does present some potential
difficulties, but even if it is incorporated into the calculations, it does not significantly affect the overall findings and
conclusions.
The main sources of random error were the Bieberometer and the Calendar, but both of these are small relative to
the measurements made and so do not have a significant impact on the reliability of the results. No sources of
systematic error were identified.
There are no major weaknesses in the experiment but there are three significant limitations:
1. The sample of music collections chosen was very narrow and so it is unclear whether the findings apply to
other groups – for example boys, adults, those with high IQs etc
2. It is unclear exactly how the music quality changes – does it change slowly at first and then faster as time
goes on, or fast at first and then slower as time goes on, or is it a steady change?
3. It is unclear what are the limits of the music quality change – does it reach a floor or does it keep on
dropping?
Improvements
To improve upon breadth of the findings, a much greater number of individuals should be studied (c. 1000) with a
random mix of the controlled variables. A multivariate regression analysis could be conducted to tease out the effect
of different factors.
To understand how the music quality changes over time, the quality of the music should be measured at monthly
intervals over the course of the experiment rather than simply at the beginning and the end.
To determine the limits of the quality change, a much greater range of Bieber songs should be added. For ethical
reasons this would be need to be capped at around 100 songs as it is unlikely that anyone could survive the minddestroying stupidity that this would cause.