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When would you use descriptive over inferential statistics
When would you use descriptive over inferential statistics
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According to Shaughnessy, Zechmeister, and Zechmeister, 2009, “in applied behavioral analysis the methods developed within the experimental analysis of behavior are applied to socially relevant problems (Shaughnessy, Zechmeister & Zechmeister, 2009, p. 317).” In this paper I will discuss some of these experimental methods used in applied research. First, I will discuss the similarities and differences between descriptive and inferential statistics, and when they should be used. In addition, I will explain the similarities and differences between single-case and small N-research designs. Furthermore, I will explain when single-case and small-N-research designs are used. Moreover; I will examine true experiments and examine how they control threats to internal validity. In addition, I will examine how true experiments are different from experimental designs. Finally, in this paper, I will discuss quasi-experiments by explaining their importance and how they differ from experimental designs.
According to Shaughnessy, Zechmeister, and Zechmeister (2009), data analysis and statistics play a major role in the analysis and the interpretation of experimental findings. Descriptive statistics and inferential statistics are both used to describe the results of an experiment. In addition, they are used to confirm that an independent variable has an effect on behavior. Furthermore, both descriptive statistics and inferential statistics are used in the stages of data analysis of an experiment. Moreover, Descriptive statistics are used in inferential statistics (Shaughnessy, Zechmeister & Zechmeister, 2009).
Differences between descriptive statistics and inferential statistics exist. For example, descriptive statistics are used to help r...
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...nd how they control the internal validity of an experiment, and how they differ from experimental designs. Finally, I discussed quasi- experiments by discussing their importance and examining how they differ from experimental designs.
References
Works Cited
Aeschleman, Stanley, R. (1991). Single-subject research designs: some misconceptions. Rehabilitation Psychology. 36(1). Pp. 43-49. Retrieved February 6, 2010 from University of Phoenix PsycArticles Database.
Kazdin, Alan, E. (1978). Methodological and interpretive problems of single-case experimental designs. Journal of Consulting and Clinical Psychology. 46(4). Pp. 629-642. Retrieved February 6, 2009 from University of Phoenix PsycArticles Database.
Shaughnessy, J., Zechmeister, E., and Zechmeister, J., (2009). Research methods in psychology. (8th ed.). New York: McGraw Hill. Chapters 7, 10, & 11.
Within the target site of the experiment, researchers wanted to answer their hypothesis; hypothesis was that increased police
American Psychological Association. (2001) Publication Manual of the American Psychological Association (5th ed). Washington, DC: McLaughlin & Reinking
There are many different factors to consider that play a part in experimental procedures. Without these variables, researchers would have a hard time making a claim about a particular topic, because they did not consider all sides of the experiment. An example of the variations done in experiments can be seen throughout Solomon Asch’s “Opinions and Social Pressure,”
Quasi-experimental designs are experimental designs that do not provide for the full control of extraneous variables. Primarily, the absence of control in this design is due to the lack of random assignment to groups. Quasi-experimental research designs are used in the study of cause and effect by manipulating the independent variable.
Going into details of the article, I realized that the necessary information needed to evaluate the experimental procedures were not included. However, when conducting an experiment, the independent and dependent variable are to be studied before giving a final conclusion.
The final chapter of this book encourages people to be critical when taking in statistics. Someone taking a critical approach to statistics tries assessing statistics by asking questions and researching the origins of a statistic when that information is not provided. The book ends by encouraging readers to know the limitations of statistics and understand how statistics are
... objective in nature, thus producing accurate data. Nevertheless, Allington and McGill-Frazon established that “reduction of a complex phenomenon to a few quantifiable variables can lead to over simplification of the phenomenon” (p.445). In other words, for observations to be complete, a combination of qualitative and quantitative data is necessitated in order to explain the totality of the phenomenon. An advantage of pre-test and post-tests designs is that it can be conducted with a single group or a control group. In the projected research topic, a pre-test and post-test was used with a group to maximize the internal validity. Neverthess, in the projected research topic, the experimental design is used to illustrate a cause and effect between two variables. The disadvantage is that external elements pose a threat to accuracy (Leedy & Ormrod, 2010, p.230).
Westen, D., Burton, L., & Kowalski, R. (2006). Psychology: Australian and New Zealand edition. Milton, Australia: John Wiley & Sons.
Corsini, Raymond J. (1994). Encyclopedia of Psychology. John Wiley and Sons, Inc: New York, New York.
Salkind, N. J. (2012). 100 questions (and answers) about research methods. Thousand Oaks, CA: SAGE
McKinney & Jones’ (1993) six hypotheses are clearly stated in a declarative form and expected differences between groups could be tested thr...
The father of quantitative analysis, Rene Descartes, thought that in order to know and understand something, you have to measure it (Kover, 2008). Quantitative research has two main types of sampling used, probabilistic and purposive. Probabilistic sampling is when there is equal chance of anyone within the studied population to be included. Purposive sampling is used when some benchmarks are used to replace the discrepancy among errors. The primary collection of data is from tests or standardized questionnaires, structured interviews, and closed-ended observational protocols. The secondary means for data collection includes official documents. In this study, the data is analyzed to test one or more expressed hypotheses. Descriptive and inferential analyses are the two types of data analysis used and advance from descriptive to inferential. The next step in the process is data interpretation, and the goal is to give meaning to the results in regards to the hypothesis the theory was derived from. Data interpretation techniques used are generalization, theory-driven, and interpretation of theory (Gelo, Braakmann, Benetka, 2008). The discussion should bring together findings and put them into context of the framework, guiding the study (Black, Gray, Airasain, Hector, Hopkins, Nenty, Ouyang, n.d.). The discussion should include an interpretation of the results; descriptions of themes, trends, and relationships; meanings of the results, and the limitations of the study. In the conclusion, one wants to end the study by providing a synopsis and final comments. It should include a summary of findings, recommendations, and future research (Black, Gray, Airasain, Hector, Hopkins, Nenty, Ouyang, n.d.). Deductive reasoning is used in studies...
Gravetter, F. J., & Wallnau, L. B. (2008). Essentials of Statistics for the Behavioral Sciences
Hewstone, M. Fincham, F. and Foster, J (2005). Psychology. Oxford: The British Psychological Society, and Blackwell Publishing. P3-23.
Researchers, professionals and others use statistics to prove their claims or findings. Even though statistics are not an absolute fact because the conclusion is mostly drawn from a sample group – representative of a specific population subjected to the research, it is commonly used as the basis of decision making or alternating choices in daily living, studies, works, scientific research, politics and other planning. The inventor of a documentary film called “An inconvenient truth”, Mr. Al Gore, for instance, in his campaign to educate people about the climate change, used statistics to alert people that everyone on earth is polluting the environment and should participate in solving the problem. He collected data from many different countries with an in...