Describe the error in the conclusion. Given: There is a linear correlation between the
number of cigarettes smoked and the pulse rate. As the number of cigarettes increases the
pulse rate increases. Conclusion: cigarettes cause the pulse rate to increase.
Assignment
At many times, researchers may make conclusions that are not correct or reasonable.
This is something that results from different factors resulting to finding a correlation where it
should not be existing and or finding no difference when indeed one exists. This discussion
delineates on the error in the conclusion, “cigarettes causes the pulse rate to increase”.
This conclusion is subject to question whether it is valid or not. It is very critical that
when such a conclusion is reached, there should be a systematic analysis of the data to ascertain
that indeed it is true. The quality of the study carried out matters a lot as it will determine
whether the conclusion reached exist or does not (Cozby, 2009).
Various factors must be considered in reaching this conclusion. One of the factors is
determining whether adequate sampling procedures were employed or not. The sampling size in
any study does matters as they affect the results of the study and consequently the conclusions
that will be reached (Cozby, 2009). Therefore, it is advisable to use a sizeable sample size to be
in a position to analyze the results. A large sample size in this case will help to determine
whether indeed as the number of cigarettes increases it leads to pulse increase. If this is
investigated in a large number of respondents and ascertained, then the conclusion can be
ASSIGNMENT 2
verified to be true. As per this conclusion, we cannot ascertain the size of the sample population
used in reaching the conclusion.
Inappropriate statistical test may also affected or cause the error of conclusion. There are
various assumptions of test statistics that should not be violated as this leads to incorrect
inferences about cause-effect relationship(William, 2006). Therefore, to avoid either committing
type 1 or type II errors it is important to avoid making any assumptions in the statistics tests.
This error may also be fishing and an error rate problem. Such an error usually is prone to
happen in the event that many hypotheses are tested in order to identify the significant effect. In
such scenario, where data is repeatedly tested there is higher chance that the researcher will make
an incorrect inference in terms of the existing relationship. Therefore, it is important that the
researcher have a limited number of testing the data to be able to reach a true conclusion. Still, it
is not verified how many numbers of time the researcher tested the data to reach the conclusion.
Another reason that may contribute to an error in the conclusion reached is the tendency
to fail to factor in the conditions under which these studies are carried out (William, 2006). For
example, in this conclusion, the respondents may be under pressure or may be having other
health problem that may influence the rate of pulse. Such factors may not be factored in reaching
such a conclusion leading to conclusions that may not be true. Therefore, it is very important for
the researchers, to be very sensitive when carrying out such researches and reaching conclusions.
There should be clear explanation of the condition that was in place during the study that led to
arriving at this conclusion.
Errors of conclusion may lead to misinterpretation and false conclusion that are
misleading. This problem is based or originates from the lack of sensitivity on the sampling
procedures, use of inappropriate statistic testing and measuring tools. This conclusion that
ASSIGNMENT 3
cigarette cause the pulse to increase is prone to errors because of different factors discussed. It is
therefore very important that appropriate research and research techniques are used to allow the
researcher to reach tangible conclusion that are correct and reasonable.
References
Cozby, P. (2009). Methods in behavioral research (10th ed. ed.). Boston: McGraw-Hill Higher
Education.
William, K. (2006). Threats to conclusion validity.