Factorial designs are extremely useful to psychologists and field scientists as a preliminary study, allowing them to judge whether there is a link between variables, whilst reducing the possibility of experimental error and confounding variables. The factorial design, as well as simplifying the process and making research cheaper, allows many levels of analysis. As well as highlighting the relationships between variables, it also allows the effects of manipulating a single variable to be isolated and analyzed singly.

Advantage of Factorial Design: Factorial design enables the researcher to manipulate and control two or more independent variables simultaneously. By this design, we can study the separate and combined effect of number of independent variables. Factorial design is more precise than single factor design (Kerlinger, 2007). By factorial design we can find out the independent or main effect of independent variables and interactive effect of two or more independent variables. The experimental results of a factorial experiment are more comprehensive and can be generalised to a wider range due to the manipulation of several independent variables is one experiment.

Limitation of Factorial Design: Sometimes, especially when we have more than three independent variables each with three or more levels are to be manipulated together, the experimental setup and statistical analysis become very complicated. In factorial experiments when the number of treatment combinations or treatments become large, it becomes difficult for the experimenter to select a homogeneous group.

Types of Factorial Design: Factorial experiments may be conducted either within subject or between subject. A mixed factorial design is also used in psychology. A mixed factorial design is one that has at least one within subject variable and at least one between subject variable.

(i) Within Subject Factorial Design – In an experiment by Godden & Baddeley (1975), researcher wants to study the effect of context on memory. They hypothesised that memory should be better when the condition at test are more similar to the conditions experienced during learning.

(ii) Between Subject Factorial Design – A between subject factorial design is presented in the following table. The example is 2×2 design. Separate groups of six experience each condition, thus requiring 24 subjects to get six responses to each of four conditions.

(iii) Mixed Factorial Design – Some time the researcher uses mixed factorial design. Researcher has two independent variable A and B. Variable A is the within subject variable and variable B is the between subject variable. Subject either experiences B1, once with A1 and also with A2; or they experience B2 once with A1 and also with A2

Factorial designs are extremely useful to psychologists and field scientists as a preliminary study, allowing them to judge whether there is a link between variables, whilst reducing the possibility of experimental error and confounding variables. The factorial design, as well as simplifying the process and making research cheaper, allows many levels of analysis. As well as highlighting the relationships between variables, it also allows the effects of manipulating a single variable to be isolated and analyzed singly.

Advantage of Factorial Design:Factorial design enables the researcher to manipulate and control two or more independent variables simultaneously. By this design, we can study the separate and combined effect of number of independent variables. Factorial design is more precise than single factor design (Kerlinger, 2007). By factorial design we can find out the independent or main effect of independent variables and interactive effect of two or more independent variables. The experimental results of a factorial experiment are more comprehensive and can be generalised to a wider range due to the manipulation of several independent variables is one experiment.Limitation of Factorial Design:Sometimes, especially when we have more than three independent variables each with three or more levels are to be manipulated together, the experimental setup and statistical analysis become very complicated. In factorial experiments when the number of treatment combinations or treatments become large, it becomes difficult for the experimenter to select a homogeneous group.Types of Factorial Design:Factorial experiments may be conducted either within subject or between subject. A mixed factorial design is also used in psychology. A mixed factorial design is one that has at least one within subject variable and at least one between subject variable.In an experiment by Godden & Baddeley (1975), researcher wants to study the effect of context on memory. They hypothesised that memory should be better when the condition at test are more similar to the conditions experienced during learning.(i)Within Subject Factorial Design –A between subject factorial design is presented in the following table. The example is 2×2 design. Separate groups of six experience each condition, thus requiring 24 subjects to get six responses to each of four conditions.(ii)Between Subject Factorial Design –Some time the researcher uses mixed factorial design. Researcher has two independent variable A and B. Variable A is the within subject variable and variable B is the between subject variable. Subject either experiences B1, once with A1 and also with A2; or they experience B2 once with A1 and also with A2(iii)Mixed Factorial Design –From MPC-005 Research Methods – IGNOU