Hypothesis Testing and Inferential Analysis
There are a number of procedures during the research process that are important to take into account. The two particularly significant ones are hypothesis testing and inferential analysis. Both ideas primarily relate to the way people evaluate their ideas and assumptions. The use of such techniques can assist in ensuring that research leads to correct conclusions and takes into account all the necessary information for a clear evaluation.
It is necessary to establish the definitions and descriptions of both processes, starting with hypothesis testing. It can be most aptly described as a process of inference that uses sample data to decide the validity of a hypothesis (Goodwin, 2018). This means that the use of hypothesis testing allows researcher reach broader conclusions about a certain group, or phenomenon, based on a smaller-scale representation of it (Goodwin, 2018). The procedure additionally has a number of formalized steps that are necessary to its completion. First, a specific hypothesis is made, usually regarding the effects of a particular treatment. Then, representatives of a chosen population are picked at random and assigned to treatment groups. The desired tests or evaluations are then made regarding the effects of treatment, which is them compared between groups. The multi-staged process helps to research the effectiveness of new methods, and see the specific effects they have on a population while also working within the time and resource constraints set upon all researchers.
Inferential statistics, then is another process that is relevant to data and its analysis. The method utilizes mathematics to make educated assumptions about any given information. For example, it can be used to make probability predictions (Goodwin, 2018). In addition, similarly to hypothesis testing, the analysis of samples can give a researcher information about the large population from a limited sample. Inferential statistics involve sampling – selecting specific parts of a larger population that align with research objectives.
Errors When Carrying Out a Test of Significance
When testing a hypothesis or making conclusions, there are number of potential mistakes that can lead an individual to making incorrect conclusions. In particular, two kinds of errors are commonly established – Type 1 Errors and Type 2 Errors. The first error occurs in cases where a true null hypothesis is seen as true, creating a “false positive” (Goodwin, 2018). This means that a particular outcome that should have been considered incorrect is accidentally assumed to be correct. The inclusion of an incorrect conclusion can contribute to making wrong assumptions about a given case, or incorrectly identifying the effectiveness of a particular treatment. It is very important to limit number of Type 1 errors in therapeutic practice.
The other type of errors happens when a false null hypothesis is not rejected, reducing the number of hypotheses that were proven correct. When a result is seen as not matching the research criteria despite its legibility, it can be seen as an example of a type 2 error (Goodwin, 2018). Both errors are prominent during research and testing, and should be accounted for in relevant contexts. The probability of an error occurring is commonly called its significance level, or probability, depending on the type.
Counselling Scenarios Involving Variables
During the counselling process, there are a number of considerations influencing the outcomes of treatment and patient-professional interaction. To examine these conditions, it is important to first differentiate between the different kinds of variables that exist. For example, professionalism and treatment effectiveness can be considered an independent variable. If a councillor has a high level of professionalism, they can be better prepared to interact with the patient, find solutions that are most optimal for that person or properly react to a variety of situations arising during the treatment process. This means that a level of professionalism directly affects other aspects of treatment, instead of being influenced by them. Alternatively, the strength of a patient-councillor relationship, the effectiveness of treatment and the ability of a patient to successfully improve are all dependant variables. Depending on the severity of any particular case, the actions undertaken by the professional and the responses of their patient, the variables will be subject to change. Specific methods of treatment can also be considered independent variables, as they affect other aspects of the councelling process.
In the presented research, the value of mindfulness is discussed as one of the variables during the councelling process. Mindfulness, in this case, can be characterized as the ability to take another person’s feelings and experiences to heart, emotionally relating to one’s patient to better understand their struggles. Psychotherapists can be specifically trained to develop particular personal qualities or improve the existing ones, in order to better assist their clients (Swift et al., 2017). As stated in the paper, mindfulness training can affect levels of presence in treatment sessions and generally contribute to their smooth proceeding.
However, it is also highlighted that clients do not see the influence of mindfulness on the procedure and do not generally perceive of it as an important factor. Confounding variables, then, are a different category of influence, one that has an effect on both dependent and independent variables (Swift et al., 2017). As highlighted by some research, insight can be considered a confounding variable in the process of therapy (Sondhi et al., 2016). In psychotherapy, the levels of patient insight can alter their ways of engagement with the professional, in addition to changing the outcomes of therapy as a whole. It is important to account for and consider such variables during the treatment process. Professionals propose that the use of insight can be effective at increasing patient engagement within the councelling process, as well as its formulation.
Sources of bias are the last and final consideration during the councelling process, one that can often be overlooked and neglected. Bias exists in every profession, and overcoming its effects to more efficiently deliver results to one’s client is an important part of psychotherapy. Biases stem from a variety of sources, including personal beliefs, interactions between people, prejudice, and previous experience. The last source of bias is likely the most important for the councelling profession, being responsible for a major part of misunderstandings or unwanted outcomes during therapy. A councillor bases their practice on a combination of evidence, common sense, and previous experience in their profession. This means, that, an individual’s encounters within their field shape the kinds of expectations they have working within that field. In councelling, this can often mean mischaracterising the particular problems of symptoms a person has in accordance with what is expected from them. Experience can be extremely helpful in quickly identifying the types of issues a person has, but it can additionally lead to confusion and incorrect conclusions about any given situation.
References
Swift, J. K., Callahan, J. L., Dunn, R., Brecht, K., & Ivanovic, M. (2017). A randomized-controlled crossover trial of mindfulness for student psychotherapists. Training and Education in Professional Psychology, 11(4), 235–242.
Goodwin, C. J. (2018). Research in psychology: Methods and design. John Wiley & Sons, Inc.
Sondhi, R., Chhibber, K., & Parikh, S. (2016). Insight: A confounding variable in therapy for patients with mood disorders. Journal of Depression and Anxiety, 5(4).