Causal relationship It is a relationship between two variables where a change in one variable

Dunbar, G. (2005). Evaluating Research Methods in Psychology. New Jersey: John Wiley & Sons Inc.

Statistics refers to the use of numerical information in everyday life to calculate facts and figures in limitless circumstances. In addition, statistics refers to the scientific collecting, classifying, summarizing, organizing, analyzing, and interpreting numerical data. This week the class’s objectives were to apply the steps in testing a research hypothesis, to compare the means of two or more groups, and to calculate the correlation between two variables. Learning Team D’s members have reflected on each of these issues and share their insights on these objectives.

The methodology selected provides the researcher the framework to present information in a logical manner. The methodology section answers two fundamental questions: How data was collected or created and, how the data was examined and determined (Research, n.d.)?

This discussion assignment has two components. First, choose an article from the popular news media (i.e., an article that might appear on a website meant for the general public, NOT a peer-reviewed academic article) that misinterprets correlation as causation. Why is the author’s interpretation of the topic a mistake? For this portion of the assignment, you may choose an article featured on the Correlation or Causation? website, but you do not have to. For the second portion of this assignment, choose one of the articles that you have read for your final project. Describe how the results from one of the articles (preferably a correlation) could be misinterpreted and misconstrued by a news source. What might the misleading headline be, and

1. State the type of study that was conducted (see methods section of article, it must be one of the above study types).

Reliability refers to coherence, stability and dependability in test results, generally using internal consistency to express the levels of reliability in the test. The higher reliability indicates the higher level of accordance, stabilization and dependability in test results. Reliability is the precondition of validity (Guba and Lincoln, 1981). The same findings may not generate if the same research is repeated, because many influencing factors may work in the process of research. The process of establishment in reliability research includes: the research rigorously collect and explain data in consistent investigation (internal checks); the process is transparent (sample design, field work, inquiry and rational data). Patton (1987) suggests that the use of triangulation in multiple approaches can increase the reliability in results.

This reasoning involves reading and reassessing data that has already been read and assessed. (Glaser 2009) Variables and the relationships between those variables are discovered and then noted.

Validity in research “establishes whether the results obtained meet the requirements of the scientific research method” (Shuttleworth, 2014). This research has validity because the surveys are not mandatory, and selection of each sample is through random selection using systemic sampling. Reliability in research means any "significant results are inherently repeatable" (Shuttleworth, 2014). Additionally, other researchers must be able to perform the same experiment under similar condition and achieve the same results. This research method is simple and given a random number generator; it is easily repeatable.

The last process is conclusion, interpretations, and limitations (Hagan, 2010, p. 19). Conclusions are based on several factors of the research process, validity, and reliability of the measurement (Shuttleworth, 2008). Validity encompasses the entire experimental concept and establishes whether the results meet all of the requirements of the scientific research method (Shuttleworth, 2008). Reliability is that any significant results must be more than a one-off finding and be inherently repeatable (Shuttleworth, 2008).

In the research process, one of the integral and significant aspects to consider is choosing the correct and appropriate evidence. This is rather a difficult process, as the researcher needs to select the most appropriate option from the many sources of evidences that are present in the pool of record. Moreover, it is prudent to note that evidences are not only present in several forms but also varies in quality. Therefore, the reliability of these evidences is of fundamental importance; otherwise the research process would not be able to meet its goals (Palinkas & Soydan, 2011).

There are various types of statistical validities that are applicable to research and experimentation. The three different validities in which I will be explaining about are, internal, external, and construct. Each of these validities is essential in order for the experiment to give accurate predictions and reach valid conclusions. I will also be explaining panel data, cross sectional data, experimental data, and survey experimental data. Lastly, I will explain how one of these data could be useful to me in resolving an issue that I may encounter in life.

A key component of using evidence-based practices is to review the best available data from multiple sources to ensure that a quality decisions. (Barends, Rousseau, & Briner, 2014). To identify the best available data, one can begin by questioning the validity and reliability of a study. Validity and reliability in evidence-based research is essential to the success of a research paper. Validity is concerned with the extent to which the research measures what it designed or intended to measure. (McLeod, 2013). The validity of research relates to how valuable the research findings are to the question at hand (Leung, 2015). Validity in research is the work done that is credible and believable because those sources find

The definition of correlation is “simultaneous variation in two variables,” (Conley, 2015, p. 46), while the definition of causality is “the notion that a change in one factor results in a corresponding change in another” (Conley, 2015, p. 48). Correlation is where you can observe a change in two different circumstances at the same time, while causation is when there is a reason that one variable causes another, or an action causes a result. With correlation there is a relationship between the variables, but there may be other factors involved that influence the outcome. Correlations can also be positive, or negative, depending on if the variables increase together (positive), or one increases while the other decreases (negative). However, in order to prove causation, there needs to be 3 different factors, “correlation, time order, and ruling out alternative explanations” (Conley, 2015, p. 48).

how one theorizes or makes logical sense of the relationships among several factors that have been

The world of statistics is one that may appear very precise at first glance, but with further investigation one can gather that there are many simple errors that may be made through no fault of the investigator. These discrepancies are divulged as a result of not meeting criterion required for a given value to be considered statistically valid. These requirements are numerous and similar, but ultimately, each holds a unique meaning. These include, but are not limited to, construct validity which ensures the experiment and information gathered coincide with the theory being tested. Subcategories of construct validity are inclusive of convergent and divergent validity,