Essay on Experimental Methods Used in Applied Research

Procedure: Using distilled water, premeasured containers and objects determine displacement of fluids and density of objects. Use ice and heat measure temperatures in Celsius, Fahrenheit and Kelvin.

Cozby, Paul. C., Bates, Scott. C. (2012). Methods in Behavioral Research (11th ed). New York, NY:McHraw-Hill

 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.

The single- subject design was used because the researcher paired the students to compare the students that received treatment in comparison to the students that did not receive treatment (Whitfield, 1999).

In most cases, scholars view research as large samples of subjects that are either participating in either two groups. Most research studies are considered as an experimental group whereby a treatment, independent variable (IV), or intervention is presented or a control group in which such interventions are not presented (Alberto & Troutman, 2016). Based on case study level C, Case 2, the independent variable is the treatment that is needed to change Rachel’s attitude in class. In the group designs, there is involvement of many subjects with each having an averaged performance, Dependent Variable which is comparable in the evaluation of experimental control. Therefore, Dependent variable in Rachel’s case is her behavior.

Baer, D. M. (Spring, 1968). Some Current Dimensions of Applied Behavior Analysis. Journal of Applied Behavior Analysis, 91-97.

The goal of inferential statistics is to end up rejecting the null hypothesis and concluding that a significant relationship exists; therefore, the null hypothesis always presume no relationship.

Single-subject design (p. 238) – using just one participate or very few participants to study the influence of a new procedure (2012, p. 238).

Single-subject design (p 238) only using one or a few participants for a study to see the influence on a new procedure or invention.

The last few weeks we covered descriptive statistic: the central tendency, variability, correlation and Z-score. Today’s session is a little bit different, we will be talking about statistical significance. Statistical significance is the level of risk one is willing to take to reject or accept a null hypothesis while it is true and it separate random error from systematic error. When doing a study or research, the statistical significance shows that the difference obtained were not caused by chance. Inferential statistics, the T-test, partition noise from bias by studying a random sample than the population in which we are interested and from the results we infer. The advantage of using sample than a population, it is convenient, saves time, energy and money because n is smaller than population and above all it helps to control systematic and random errors. When we are making a conclusion, we should have a certain confidence or probability of being right and that is called the alpha level; which the risk you are willing to

D., & Pear, J. J. (2014). Analysis of the interaction between experimental and applied behavior analysis. Journal Of Applied Behavior Analysis, 47(2), 380-403. doi:10.1002/jaba.124

In comparison to the reversal design mentioned in Chapter 4, the multiple baseline design is useful when testing a treatment that produces irreversible effects, such as teaching a reading technique. Similar to a reversal design, a multiple baseline design starts with a baseline condition, proceeding with a treatment condition. Alternatively, a researcher using a multiple baseline design does not repeat a baseline measurement after the treatment is implemented. This design was originally developed for behavioral psychologists (Compton, 2010), but the application has spread; this design is an informative tool for investigating changes in behavior over time.

| Based on explicit knowledge and this can be easy and fast to capture and analyse.Results can be generalised to larger populationsCan be repeated – therefore good test re-test reliability and validityStatistical analyses and interpretation are

There are six methods used to analyse trial design; of which are discussed as follows.

Quasi-experimental research, which was once considered ‘flawed’ and less superior to true experimental research, has become increasingly popular over the last three to four decades in many areas, especially the social sciences (Coolican, 2014, p. 121). It differs from true experimental research design in the way that quasi-experimental research doesn’t involve random assignment of participants to groups and often has less control over the independent variable (Follmer Greenhoot, 2003, p. 94; Coolican, 2014, p. 121). An