Scientific Report Writing

Scientific Report Writing
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ABSTRACT
The study summaries scientific analysis of given data of total energy expenditure which is
classified in two groups A and B. In study P values for Group A and Group B are determined
which help to assess the actual significance of data. Further the study comprises certain major
methods like statistical analysis, correlation etc. to better explore the relevance of study.
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Contents
ABSTRACT.....................................................................................................................................2
Contents...........................................................................................................................................3
Introduction and Aim.......................................................................................................................4
Methods and Discussion..................................................................................................................4
Conclusion.....................................................................................................................................12
REFERENCES..............................................................................................................................13
Appendix........................................................................................................................................14
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Introduction and Aim
Total energy expenditure (TEE) consists of several elements comprising physical activity
energies expenditure (PAEE), resting energies expenditure and resting metabolic rate (RMR)
and thermal impact of food (TEF). The potential to assess overall energy expenditure (TEE) as
well as its elements is incredibly essential in terms of energy balance therefore in lifestyle as well
as health-related studies. TEE tests are also important for the measurement of under-and over-
reporting of energies consumption and for the designing of experimental diets (Ndahimana and
Kim, 2017). The study covers the calculation of P values for contrast of measures among Group
B versus Group A with the addition of independent t-test. In addition, statistical analysis was
carried out on all respondents (Only participants 24 in Group-B as there are no-body masses
related data with respect to these participant).
In this study main objective is to estimate TEE, forecast RMR as well as to assess PAL. Aim
of study is to gather TEE through Physical-Activity Diaries as well as Compendium of different
Physical Activities. Moreover, study consist of prediction of RMR through applying most
appropriate RMR predictions equation.
Methods and Discussion
T-test to find out P values: The P-value method requires calculation of the likelihood of finding
a "likely" or "unlikely" in direction of an alternate hypothesis – assuming that null hypothesis
was valid. If p-value is smaller, this is "improbable" if it is less than or equal to it and, if the p-
value is higher, then that's "likely," and where a research question null hypothesis (H0) is valid –
the concept of "extreme" is based upon the testing of this hypothesis, P value is lesser than (or
equivalent to) this is "unlikely.".
P is often defined as denying H0, if it is real, but this is not clear possibility. Here, null
hypothesis becomes typically "no difference" hypertension, for example no difference among
group A and group B's blood pressures. Establish null hypothesis explicitly before the beginning
of the analysis with each study issue. If a major move in an unanticipated way is unrelated to
your analysis, the only case where you can use one sided p - values is. This is uncommon; you
choose two-sided P value if you have concern (Knapp, 2017).
Group A:
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