Quantitative And Qualitative Research M

 Inferential statistics helps us to analyze predictions, inferences, or samples about a specific population from the observations that they make. “With inferential statistics, you are trying to reach conclusions that extend beyond the immediate data alone” (Trochim, 2006). The goal for this type of data is to review the sample data to be able to infer what the test group may think. It does this by making judgment of the chance that a difference that is observed between the groups is indeed one that can be counted on that could have otherwise happened by coincidence. In order to help solve the issue of generalization, tests of significance are used. For example, a chi-square test or T-test provides a person with the probability that the analysis’ sample results may or may not represent the respective population. In other words, the tests of significance provides us the likelihood of how the analysis results might have happened by chance in a scenario that a relationship may not exist between the variables in regards to the population that is being studied.

This paper primarily concerns qualitative research, but we were asked to compare both qualitative and quantitative methods. During comparison, there are many noted differences in both study designs, but not many similarities. Qualitative research uses a subjective approach with a large sample population. It collects non-statistical data, using an unstructured or semi-structured technique (Nieswiadomy & Bailey, 2018). Quantitative research uses an objective approach and large, random, sampling to ask opinions in a structured way. The findings of quantitative studies are conclusive and used to recommend a final course of action (Nieswiadomy & Bailey, 2018). While it is hard to see similarities between the two, both methods aim to find a solution to a problem or question, the researcher doing the study may affect the outcome and an analysis of the collected data must be done (Souza, 2017). What many don’t realize is the connection amongst the two. You can say, both types of research build upon one another, meaning quantitative studies can quantify results found in qualitative research (Souza, 2017).

Compare and contrast quantitative and qualitative methods on each of the elements listed. Please use scholarly, academic literature to support your response.

In order to know whether the evidence of research studies are accurate, one must be able to have a fundamental understanding in statistical analyses to determine if such descriptions and findings within manuscripts and articles are presented correctly and explicitly (Sullivan, 2012). Proper use of statistics begins with the understanding of both descriptive and inferential statistics. Correct organization and description of data characteristics from the population sample being studied leads the researcher to identify a hypothesis and formulate inferences about such characteristics. It is with inferential statistics that researchers conduct appropriate tests of significance and determine whether to accept or reject the identified null

Researchers tend to draw conclusions and/or generalizations from the sample of participants in order, to generalize about others that are not in the specific study (Trochim & Donnelly, 2008). Therefore, it is essential that researchers learn

with significant results possibly being a side effect of large sample sizes. Further there were

In population-based studies, instead of looking at a small group of individuals to make an assumption on the entire population, we are taking numbers that represent the population and determining

2. Discuss the generalizability and validity of the study. For example, will findings of this study generalize to other people and/or situations, can we generalize from the study participants to the general population, and do the methods employed have validity?

*For accurate inference, researchers need to analyze data drawn from representative samples. Discuss some of the practical limitations to doing so for qualitative and quantitative approaches.

2. Inferential statistics refers to generalizing from a sample to a population, estimating unknown parameters, drawing conclusions, and making decisions.

Regardless of whether the study is descriptive or experimental, the extent to which a study's results can be generalized or applied to other people or settings reflects its external validity. Group research engaging randomization will initially possess higher external validity than will case studies and single-subject experimental research that do not use random selection for the assignment.

A key strength for a study having high ecological validity is that it allows psychologists to generalise the findings; showing how behaviour is affected in real-life or with real life tasks. Therefore, the researcher can ensure that the practical

Although, the results of the study can generalize to similar population, the further research should be done with larger samples and setting other than laboratory.

Quantitative research involves collecting data, which can be expressed numerically. The design is well structured with pre-determined outcomes. It frequently involves testing a hypothesis, which then can be analysed from the data deductively using statistical methods. Using numerical data is easier to analysis mathematical, so larger sample sizes can be utilised compared to qualitative research, therefore giving a better representative of the population; along with simplifying the process of making a generalisation. Another advantage is that studies can easily compare to similar findings (Kruger, 2003). The disadvantages are the results are limited and might not provide a proper understanding of the topic. Also, statistics and leading questions can be used to give a false representation of the data when summarising.

a. Conclusion drawn must be based on a sample that represent the entire group .