You are to design an observational experiment with at least three (3) between-su

Question

You are to design an observational experiment with at least three (3) between-subjects conditions of one independent variable that can be analyzed with an ANOVA. Your experiment cannot involve doing anything to any humans or animals, because that requires institutional approvals that are beyond the scope of this class. You might choose to observe the behavior of people or animals in a public place (without actually doing anything to them) or you could analyze something broadcast over television or the Internet. You could also analyze objects rather than people or animals. You should have between five (5) and ten (10) subjects or observations in each condition of your independent variable. Please do not collect data or conduct calculations until you receive feedback from your instructor for this part of the assignment.

Explanation / Answer

Independent variables are those variables that are explanatory variables, that means these variables explain the variation in the dependent variable or response variable. For example, I take the length of filament extruded from a 3d printer, it depends on the nozzle diameter, nozzle temperature, filament diameter, filament material etc. So the nozzle diameter, nozzle temperature, filament diameter, and filament material are the independent variables that explain the variation in the length of the filament extruded out from the nozzle. In ANOVA design, these independent or explanatory variables are categorical data, called as factors that influences or explains the variation in the extruded length. Example, nozzle diameter has categories such as 0.4mm, 0.7mm, 1.0mm diameters, and filament diameters are 1.75mm and 3.0mm standard diameter available in the market, filament materials are ABS, PLA, Nylon, PC, PVA, etc..

Conditions of the dependent variables are their categories, each will be an level in the independent variable. For example filament material is ABS is a condition, PLA is an another condition of the independent variable.

Dependent varaibles are the reponse variable that I am interested to compare the length of the extruded length under various conditions of the factors or independent variables. Dependent variables are the end result, as in simple linear regression, y=mx+c, y is the dependent varible, it depends on the position of the x. Here in linear regression, x is continuous data, whereas in ANOVA those are categorical data. Dependent varibles are groups, in fact with the best combination of all the conditions of the factors, we will have a premium, or standard quality 3d printers.

Dependent variables are assumed to have better qualities with the condition of matching our design requirements. Only incoming inspection of the material quality, color of the filament, etc. Temperature is also set as 185*c, 195deg c at different interval till 245deg C.

Levels are the categories or type of dependent variables. For example, nozzle diameter of 0.4mm or 0.7mm used in the experiment at two levels to measure the extruded length.

ANOVA is the best model for analysing the different gropus of the independent variables under varions conditions and levels of the dependent variable. For example, Group1 has a set of conditions and levels like, 1.75mm orange color filament, 0.4mm nozzle diameter, filament material is PLA; GroupII: 1.75mm black color filament, 0.7mm nozzle diameter, material is ABS. and keeping other factors common for both the groups. ANOVA analysis the variation within the group means at different factors, and variations among the various groups. If the variation is different from group to group, then it is easy to identify which group is better,

Sample mean, sample size, sample standard deviation, sample variance, standard error are the sample descriptive statistic, I will use for doing the calculations related to variation within groups, among groups using least sum squares methods, and mean square errors, then the F-statistics, F critical statistics, probability of the level of significance for the degrees of freedom of the sample to test the proposition.

Confounding variables are those environmental factors here that are assumed as under normal room temperature, input voltage 240V 60 hz, indoor applications, etc.

Related Questions

Navigate

• Browse (All)
• Browse Y
• Subjects

Integrity-first tutoring: explanations and feedback only — we do not complete graded work. Learn more.