The Research Concept
Name
Institutional Affiliation
The Concept of Research
Research is the careful deliberation of study regarding a particular issue or concern using different methodologies and making a different hypothesis. This paper will entail the various examples of how the research uses hypothesis testing and describe the criteria for rejecting a null hypothesis. Moreover, it will capture the importance of the above mentioned during hypothesis testing.
In this context, the hypothesis is used in inferring the gotten results of interpretation that was performed on a sample data from a vast population. The information shows the researcher whether the explanation is genuine true or false. The different examples used in hypothetical testing involve the use of the null hypothesis and the alternative interpretation (Schneider, 2015). These are done when a predetermined number of subjects in assumption gives the alternative explanation. Notably, these depicts that the original hypothesis may be overturned or rejected. Therefore, before making any hypothesis, decide the level of statistical significance in the given interpretation since you cannot be 100% perfect in your findings.
Additionally, the null hypothesis may be disallowed when the p-value is less than or equals to the required value. These causes the null hypothesis being excluded in favor of an alternative explanation (Greenland et al., 2016). Casually, the null hypothesis only occurred by chance. On the other side, if the P-value is higher than the absolute value, the null hypothesis will not be vetoed and is said to be true.
The significance of the research mentioned above hypothesis in my practice and with patient interaction is that they provide and explain an estimated account of the singularities (Greenland et al., 2016). The importance is to give the investigator an interpersonal report directly tested in the research study.
Reference
Greenland, S., Senn, S. J., Rothman, K. J., Carlin, J. B., Poole, C., Goodman, S. N., & Altman, D. G. (2016). Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations. European journal of epidemiology, 31(4), 337-350.
Greenland, S., Senn, S. J., Rothman, K. J., Carlin, J. B., Poole, C., Goodman, S. N., & Altman, D. G. (2016).
Schneider, J. W. (2015). Null hypothesis significance tests. A mix-up of two different theories: the basis for widespread confusion and numerous misinterpretations. Scientometrics, 102(1), 411-432.
The Research Concept
Name
Institutional Affiliation
The Concept of Research
Research is the careful deliberation of study regarding a particular issue or concern using different methodologies and making a different hypothesis. This paper will entail the various examples of how the research uses hypothesis testing and describe the criteria for rejecting a null hypothesis. Moreover, it will capture the importance of the above mentioned during hypothesis testing.
In this context, the hypothesis is used in inferring the gotten results of interpretation that was performed on a sample data from a vast population. The information shows the researcher whether the explanation is genuine true or false. The different examples used in hypothetical testing involve the use of the null hypothesis and the alternative interpretation (Schneider, 2015). These are done when a predetermined number of subjects in assumption gives the alternative explanation. Notably, these depicts that the original hypothesis may be overturned or rejected. Therefore, before making any hypothesis, decide the level of statistical significance in the given interpretation since you cannot be 100% perfect in your findings.
Additionally, the null hypothesis may be disallowed when the p-value is less than or equals to the required value. These causes the null hypothesis being excluded in favor of an alternative explanation (Greenland et al., 2016). Casually, the null hypothesis only occurred by chance. On the other side, if the P-value is higher than the absolute value, the null hypothesis will not be vetoed and is said to be true.
The significance of the research mentioned above hypothesis in my practice and with patient interaction is that they provide and explain an estimated account of the singularities (Greenland et al., 2016). The importance is to give the investigator an interpersonal report directly tested in the research study.
Reference
Greenland, S., Senn, S. J., Rothman, K. J., Carlin, J. B., Poole, C., Goodman, S. N., & Altman, D. G. (2016). Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations. European journal of epidemiology, 31(4), 337-350.
Greenland, S., Senn, S. J., Rothman, K. J., Carlin, J. B., Poole, C., Goodman, S. N., & Altman, D. G. (2016).
Schneider, J. W. (2015). Null hypothesis significance tests. A mix-up of two different theories: the basis for widespread confusion and numerous misinterpretations. Scientometrics, 102(1), 411-432.
The Research Concept
Name
Institutional Affiliation
The Concept of Research
Research is the careful deliberation of study regarding a particular issue or concern using different methodologies and making a different hypothesis. This paper will entail the various examples of how the research uses hypothesis testing and describe the criteria for rejecting a null hypothesis. Moreover, it will capture the importance of the above mentioned during hypothesis testing.
In this context, the hypothesis is used in inferring the gotten results of interpretation that was performed on a sample data from a vast population. The information shows the researcher whether the explanation is genuine true or false. The different examples used in hypothetical testing involve the use of the null hypothesis and the alternative interpretation (Schneider, 2015). These are done when a predetermined number of subjects in assumption gives the alternative explanation. Notably, these depicts that the original hypothesis may be overturned or rejected. Therefore, before making any hypothesis, decide the level of statistical significance in the given interpretation since you cannot be 100% perfect in your findings.
Additionally, the null hypothesis may be disallowed when the p-value is less than or equals to the required value. These causes the null hypothesis being excluded in favor of an alternative explanation (Greenland et al., 2016). Casually, the null hypothesis only occurred by chance. On the other side, if the P-value is higher than the absolute value, the null hypothesis will not be vetoed and is said to be true.
The significance of the research mentioned above hypothesis in my practice and with patient interaction is that they provide and explain an estimated account of the singularities (Greenland et al., 2016). The importance is to give the investigator an interpersonal report directly tested in the research study.
Reference
Greenland, S., Senn, S. J., Rothman, K. J., Carlin, J. B., Poole, C., Goodman, S. N., & Altman, D. G. (2016). Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations. European journal of epidemiology, 31(4), 337-350.
Greenland, S., Senn, S. J., Rothman, K. J., Carlin, J. B., Poole, C., Goodman, S. N., & Altman, D. G. (2016).
Schneider, J. W. (2015). Null hypothesis significance tests. A mix-up of two different theories: the basis for widespread confusion and numerous misinterpretations. Scientometrics, 102(1), 411-432.
