However, inductive reasoning
is not always valid. Assuming general principles are viable on a limited number
of cases, could be erroneous.

Furthermore, trends that we observe could possibly be explained by data from
other phenomena. This may result in false cause fallacy. In statistics, it is
essential to note that correlation between two variables is not equal to
causation. A personal example is my Biology Extended Essay. My essay aimed to
find the effect of increasing concentration of potassium sulfate on the growth rate
of Oregano. I hypothesized a strong positive correlation on the growth rate
with increasing fertilizer solution, but what I observed was a negative correlation
instead. It was not until I analyzed the leaves of the plants with a microscope,
that I saw spider mites eating the possibly the chlorophyll of the leaves,
forming white spots. This, among other uncontrolled factors, may have contributed
to reduced growth. Thus, there are several potential external or hidden
variables that contribute to the correlation. I cannot say for certain that
increasing potassium sulfate reduces the growth rate of Oregano. Assuming
correlation is causation therefore leads to statements of generalization. An
example of generalization are parental concerns over
vaccination safety – vaccinations being linked to autism spectrum disorders. Although
no vaccine is completely harmless, the belief in this causal link originates from
parental concern, fed by confirmation bias and past experiences. This is where
the observation of uniformities is not effective, as making conclusions based
on biased correlation does not imply causation. Rather, it is the cofounding factors between cause
and effect that can lead us beyond our immediate sense perception.

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Past experiences, hence, our
memories play a role as a guide to future predictions. We place confidence in
past correlations to make propositions about future correlations by our
knowledge that nature is, generally, uniform. The past, in relevant respects,
is like the future. Adding to the inductive argument; if “every day in the past
the sun rose, then tomorrow the sun
will rise”. Here, we make the assumption that nature is uniform – that the
future will be like the past. This supports earlier inductive arguments and
adds to the principle of uniformity. In another example, analysts have
predicted how many medals each country would win in the 2012 Olympics, based on
past performances from the 1996 and 2008 Olympic games as well as
socio-economic variables (GDP, population size…).1
The models they produced predicted Olympic successes fairly well when compared
to the actual medals earned for the 2012 Olympics.2
Our experiences yield information that allows us to predict possible future
outcomes.

1 Bredtmann, J., Crede, C. J. and
Otten, S. (2016). Olympic medals: Does
the past predict the future?. Significance, 13: 22–25.

doi:10.1111/j.1740-9713.2016.00915.x

2 Bredtmann, J., Crede, C. J. and
Otten, S. (2016). Olympic medals: Does
the past predict the future?. Significance, 13: 22–25.

doi:10.1111/j.1740-9713.2016.00915.x