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    Factorial research designs are experiments that involve factorial combinations of independent variables. Factorial combinations involve pairing each level of one independent variable with each level of a second independent variable. Factorial combinations make it possible to determine the effect of each independent variable alone (main effect) and the effect of the independent variables in combination (interaction effect). The simplest possible experiment involves one independent variable manipulated

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    Experimental designs Experimental designs are viewed as the most accurate, and most demanding of research designs, requiring strict attention to rules and procedures. Researchers use these research designs to manipulate and control testing procedures as a way to understand a cause and effect relationship. Commonly, independent variables are manipulated to judge or decide their effect on a dependent variable (Trochim & Donnelly, 2008). In order for an experiment to be considered a true experimental

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    Applied Research

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    Applied Research Experimental and descriptive research designs, statistics, and inferences in psychological settings and methods differ in many ways yet have similar qualities. All psychological research follows ethical codes and regulations. Each type of experiment discussed contains similarities and differences. The importance of each research method for individuals and societies varies according to the need addressed in creating the project. Beneficial interventions and treatments are developed

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    Experimental Methods Used in Applied Research

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    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,

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    Exploring the Logic of Experimental Design

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    because if an experiment has good internal validity without any confounds, then there is only one explanation for the results of the experiment. External validity is occurs when experimental results can be generalized to other situations and subjects or behaviors correlate to those behaviors external to the study (Jackson, C., 2012). External validity helps determine if findings can be generalized to different persons, environments, measures, settings, or times. 6. Within-subject design uses the same

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    Don't Drive and Talk on the Cell lPhone

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    research using experimental designs and controlled conditions. Experimental design, also known as experiments, permit cause-and-effect inferences. This is the best research design for testing this hypothesis as researchers have the ability to manipulate variables, such as cell phone use, and to see their affect on driver behavior. The main idea is that it is a controlled form of research, whereas correlational experiments, case studies, or naturalistic observation research designs include/measure preexisting

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    experimental design that fits their needs. Even though experiments may share characteristics, “their use and application vary depending on the type of design used” (Creswell, 2008, p. 310). Therefore understanding the types of experimental designs commonly used to inquiry about educational thematic is useful to identify the design whose approach will contribute the success of the research. The two major umbrellas of experimental design include between-group and within-group designs, which are further

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    instead of exposure to the drug itself. The drug effect theory has used before-and-after experiments. There are two groups in the before-and-after design experiment. The first group: the subjects receive drug after they tested on criterion on each tolerance trail. The second group: the subjects receive drug before they tested on criterion to react on each tolerance trail. As the results of the before-and-after experiment according to the drug-effect theory, tolerance is significantly greater in the group

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    Review of paper 1

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    1. Introduction Design variables are important to be conducted the appropriate experiment analyzing and getting the accurate values for integer, discrete, zero-one (binary), and continuous variables. The researchers should classify design factors before the experiment is conducted. In literature, there are several factors such as quantitative, qualitative, discrete, continuous, zero-one (binary), non-zero-one (non-binary), controlled and uncontrolled variables (Sanchez & Wan, 2009). Quantitative

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    1. Explain robust design, quality loss function, system design, parameter design, tolerance design Answer: 1.1. Robust design: Though robust design can be explained in different way, it can be generalized to: one step/stage of product design development process at which design experiment is made on multiple factors so that to minimize the effects of variation without avoiding the causes (since they are too difficult or too expensive to control). 1.2. Quality loss function: It is an equation

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