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Design and analysis of experiment: Aim of Experiment and Experiment in detail
- 1. Design and analysis of experiment - * Aim of experiment and experiment in detail. Name- Mukesh Vinod Kapse Class- B pharmacy 4 th year, Vlll th sem Roll no- 31 Subject- Biostatistic and research methodology Hi tech college of pharmacy, chandrapur
- 2. Content - Introduction Objective Scheme of experiment Definition of Aim of experiment Experiments Terminology Principles of experiment Steps of designing experiment Reference
- 3. Introduction-> The Design of Experiments is carried by various methods using different tools and techniques in which Response Surface Method is one. These strategies were originally developed for the model fitting of physical experiments, but can also be applied to numerical experiments. Objectives : The objective of Design of Experiments is the selection of the points where the response should be evaluated. Most of the criteria for optimal design of experiments associated with the mathematical model of the process.
- 4. Scheme of experiment : Investigation is the process that is used to find something better from the existing system Investigators performed experiments in all fields of enquiry to discover something about a process or system. An experiment is a test or series of tests in which desired changes made to the input variables of a system or process so that reasons are may identify and observed for changes that may also be observed in the output response. Experiments are performed to analyse the situation and obtaining output responses which may further modified according to need.
- 5. Definition of Aim of experimet : When the aim is well defined in concurrence with the situation,the problem should be analysed with the help of the following questions: What is known? Whatis unknown? What do we need to investigate? To be able to plan the experiments in a rational way the problem has to be concrete. Which experimental variables can be investigated? Which responses can be measured?
- 6. Experiments : Experiments are actions that are carried out in order to examine the behaviour of the system and the influences of factors on the system under study. In statistical experimental design all experiments are determined in advance. This means that in each experiment all the factors have defined values. The evaluation of calculated effects is possible only if the experimental error is determined via variabiity. The sources of variability are different and can include analytical Procedure, technological processes, sample preparation processe, storage condition, packaging, ect
- 7. Before starting any experiment four preliminary activities must be carried out: -Identification of all factors that may affect the system. -Selection of the most significant factors on the basis of known facts, data from literature, experience etc. -Determination of the levels of all selected. -Selection of significant response parameters. The above activities should be carried out by experts from different fields (technology, stability, analytics, etc) so that all aspects are examined carefully before starting experiments. Although time-consuming,these activities can save money and time, if carefully and thoroughly done for further, so called technical activities.
- 8. The following steps are carried out in the technical activities 1) Selection of suitable experimental design. 2) Experimental work. 3) Factor analysis.
- 9. Terminology: To simplify the communication a few different terms are introduced and defined. Experimental domain: The experimental 'area that is investigated(defined by the variation of the experimental variables). Factors: Bperimental variables that can be changed independently of each other. Independent variables: Same as factors. Continuous variables: Independent variables that can be changed continuously. Discrete variables: Independent variablesthat are changed step-wise. Responses: The measured value of the resultsfrom experiments. Residual: The difference between the calculated and the experimental result.
- 11. Steps in designing experiment : qualitative understanding that the how these data are to be analysed 1 Recognition of and statement of problem. 2. Selection of the response variable. 3. Choice of factors, level and range. 4.Choice of experimental design. 5. Performing the experiment. 6. Statistical analysis of the data. 7. Conclusions and recommendations. 8.Feedback from the users who uses the concluding res端lt of an experiment for further analysis and improvement.
- 12. Reference : "Biostatistic and research methodology" by Dr vinod kumar, Dr sanjay sharma,Dr deepak kumar,PeeVee publication,page no 227-233.
- 13. Thank you