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Mixed design experiment

Mixed designs make use of already-present variables and manipulate a second variable. This is also referred to as a quasi-experimental or natural design. Subjects are not randomly assigned to groups; they automatically fall into one of those categories. Mixed designs are used when a result is further distinguished by another independent variable In statistics, a mixed-design analysis of variance model, also known as a split-plot ANOVA, is used to test for differences between two or more independent groups whilst subjecting participants to repeated measures Mixed‐Methods‐Designs sind ein Spezialfall der Triangulation im allgemeinen Sinne und bezeichnen die Kombination von Elementen qualitativer und quantitativer Forschung in ein und derselben Untersuchung This is known as a mixed design. You can extend the hierarchical linear model (see the last tutorial) to incorporate predictors that have been measured with different entities. However, as with repeated measures designs, when the goal is to compare means people often apply a variant of this model that is often referred to as Mixed ANOVA Das Triangulationsdesign ist das am häufigsten eingesetzte Design im Bereich Mixed-Methods. Es ist dadurch gekennzeichnet, dass qualitative und quantitative Verfahren der Datenerhebung miteinander kombiniert werden. Die Daten beziehen sich dabei auf dasselbe Forschungsinteresse und es wird ihnen das gleiche Gewicht zugeschrieben

Description of the experiment: Participants will be asked to watch 3 movie clips (30-60 sec each). After watching each clip, they will be presented with 3 possible scenarios of how the plot will unfold. We ask the participants to choose one scenario for each movie clip based on their perception The field of mixed methods has only been widely accepted for the last decade, though researchers have long been using multiple methods, just not calling them mixed. Mixed methods research takes advantage of using multiple ways to explore a research problem Einstieg in die mixed ANOVA Die mixed ANOVA ist eine der wichtigsten Formen der Varianzanalyse und kommt vor allem im klinischen und medizinischen Rahmen zum Einsatz. Die mixed ANOVA verbindet within-subject und between-subject Designs und hat daher auch ihren Namen

In jeder Zelle befindet sich jetzt eine Faktorstufenkombination. Für diese braucht man jeweils eine Untersuchungsstichprobe. In einem 2x2-faktoriellen Design benötigt man 4 Gruppen, in einem 2x3x2-faktoriellen Design benötigt man schon 12 Gruppen. Nach Sarris (1992) sollte man in einem mehrfaktoriellen Randomisierungsdesign pro Zelle etwa 5-15 Versuchspersonen einplanen. Die Präzision steigt dabei mit zunehmender Probandenanzahl. Durch die Untersuchung von mehr als eine Mixed level design experiments are generated using Pseudo-factors To determine the number of runs required to estimate each possible factor and interaction in a mixed-level design, multiply the number of runs calculated separately for each fixed-level case Im Jahr 1951 wurden die faktoriellen Versuchspläne von George E. P. Box und K. B. Wilson durch Methoden für Wirkungsflächenpläne ergänzt, die besser zu den Anforderungen von industriellen Experimenten passten. J. Kiefer stellte 1959 einen formalen Ansatz zur Auswahl eines Versuchsplans vor, der auf objektiven Optimalitätskriterien basiert. Durch die Einführung von Optimierungsansätzen konnte sich das Anwendungsgebiet auf die Verfahrensoptimierung in der chemischen. Mixed methods research is more specific in that it includes the mixing of qualitative and quantitative data, methods, methodologies, and/or paradigms in a research study or set of related studies. One could argue that mixed methods research is a special case of multimethod research

Regression designs and mixed-effects modelling 177 2. Comparing experimental designs: factorial and regression designs Factorial designs are based on experimental control between groups of experimental items, so-called conditions. In the simplest case, all potentially relevant variables are controlled except one variable of interes In a factorial design, each level of one independent variable is combined with each level of the others to produce all possible combinations. Each combination, then, becomes a condition in the experiment. Imagine, for example, an experiment on the effect of cell phone use (yes vs. no) and time of day (day vs. night) on driving ability A mixed factorial design involves two or more independent variables, of which at least one is a within-subjects (repeated measures) factor and at least one is a between-groups factor. In the simplest case, there will be one between-groups factor and one within-subjects factor

The choice of experimental design will affect the type of statistical analysis that should be used on your data. It is possible that an experiment design is both within-subjects and between-subjects. For example, assume that, in the case of our car-rental study, we were also interested in knowing how participants younger than 30 perform compared with older participants. In this case we would have two independent variables An experiment is a type of research method in which you manipulate one or more independent variables and measure their effect on one or more dependent variables. Experimental design means creating a set of procedures to test a hypothesis. A good experimental design requires a strong understanding of the system you are studying Versuchsplanung mit JMP ® Die Versuchsplanung (Design of Experiment, DOE) ist ein praktischer und überall einsetzbarer Ansatz für die Erforschung von Möglichkeiten, die von mehreren Faktoren abhängen. JMP bietet marktführende Leistungsmerkmale für die Planung und Analyse in einer Form an, die eine leichte Bedienbarkeit garantiert A presentation over the research design Mixed Methods Designs. Covers the definition, how it developed, key characteristics, types of designs, steps in condu.. The available mix design methods are mostly dependent on charts, graphs and empirical relations from repetitive experiments following the same principle with a little bit of variations in different mix methods. Some of the commonly known design methods are-1. Trial and Adjustment method of mix design 2. British DoE mix design method 3. ACI mix design method 4. Concrete mix proportioning-IS.

What Is a Mixed Design in Psychology? - Reference

13.8 Design • Design: An experimental design consists of specifying the number of experiments, the factor level combinations for each experiment, and the number of replications. • In planning an experiment, you have to decide 1. what measurement to make (the response Mixed-method tools allow for more flexible evaluation design options, with a possibility of combining evidence in various ways, as dictated by the purposes of an investigation and object of inquiry. The advantages and disadvantages of mixed-method designs stem from the properties and limitations of particular quantitative or qualitative. DOE (design of experiments) helps you investigate the effects of input variables (factors) on an output variable (response) at the same time. These experiments consist of a series of runs, or tests, in which purposeful changes are made to the input variables. Data are collected at each run Experimental Designs; Semi-Experimental Designs; Quasi Experiment; Qualitative (Flexible) Research Design. Cresswell (1994) has defined qualitative research as, Qualitative research is an inquiry process of understanding based on distinct methodological traditions of inquiry that explore a social or human problem. The researcher builds a complex, holistic picture, analyzes words, reports.

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How to design mixed Taguchi experiment orthogonal array having 2 factors 3 levels and 2 factor 2 level Design Of Experiments courses from top universities and industry leaders. Learn Design Of Experiments online with courses like Design of Experiments and Experimental Design Basics Mixed Designs When a study has at least one between-subjects factor and at least one within-subjects factor, it is said to have a mixed design. Let's begin with a common within-subjects factor: time. In a pre-post design, subjects are measured both before and after some treatment is applied. For example, Read writing about Experiment in Mixed Design. Exploring how VR can be used as a design tool, in the different steps on the way to a final design

To design a mixed study, researchers must understand and carefully consider each of the dimensions of mixed methods design, and always keep an eye on the issue of validity. We explain the seven major design dimensions: purpose, theoretical drive, timing (simultaneity and dependency), point of integration, typological versus interactive design approaches, planned versus emergent design, and design complexity. There also are multiple secondary dimensions that need to be considered. Browse other questions tagged mixed-model experiment-design random-effects-model ordinal-data or ask your own question. Featured on Meta State of the Stack Q1 2021 Blog Post. Stack Overflow for Teams is now free for up to 50 users, forever. Should we replace the data set request with distinct this is an off-topic Related. 8. Mixed effects model or mixed design ANOVA in R. 4. Repeated. Design of Experiments is particularly useful to: •evaluate interactions between 2 or more KPIVs and their impact on one or more KPOV's. •optimize values for KPIVs to determine the optimum output from a process. Design of Experiments is particularly useful to: •evaluate interactions between 2 or more KPIVs and their impact o for the suitable mix design have been specified by the Asphalt Institute. 11.2 OBJECTIVE To design the Asphalt concrete mix using Marshall method. 11.3 MARSHALL METHOD OF MIX DESIGN In this method, the resistance to plastic deformation of a compacted cylindrical specimen of bituminous mixture is measured when the specimen is loaded diametrically at a deformation rate . 53 of 50 mm per minute. Experimental research is the most familiar type of research design for individuals in the physical sciences and a host of other fields. This is mainly because experimental research is a classical scientific experiment, similar to those performed in high school science classes

Mixed-design analysis of variance - Wikipedi

  1. istered battery of tests is completed at four time points: baseline, postintervention and follow-up at 1-month and 2-month postinterventions.
  2. Sie bezeichnet eine Reihe von Forschungsdesigns, bei denen Manipulationen und kontrollierte Versuche durchgeführt werden, um kausale Prozesse zu verstehen. Im Allgemeinen werden eine oder mehrere Variablen manipuliert, um deren Auswirkung auf eine abhängige Variable zu bestimmen
  3. • Design: An experimental design consists of specifying the number of experiments, the factor level combinations for each experiment, and the number of replications. • In planning an experiment, you have to decide 1. what measurement to make (the response) 2. what conditions to study 3. what experimental material to use (the units
  4. Experimental Procedure 1. For strength requirements, select the water to cement ratio by weight. 2. Before mixing concrete, be sure that the mixer has been buttered with a mixture of cement, sand, and water. 3. Divide your water into two buckets, one with about 3/4 of the water. Put about half the coarse aggregate and the 3/4-bucket of water. 4. Start the mixer
  5. Mixture experiments involve components of a mixture, where the levels of the components are constrained to sum to 100% (or some other fixed value). Upper and lower constraints may be specified for each component. Included are simplex-lattice, simplex-centroid, and extreme vertices designs

When the factors are proportions of a blend, you need to use a mixture design: In a mixture experiment, the independent factors are proportions of different components of a blend. For example, if you want to optimize the tensile strength of stainless steel, the factors of interest might be the proportions of iron, copper, nickel, and chromium in the alloy. The fact that the proportions of the different factors must sum to 100% complicates the design as well as the analysis of mixture. mixed factorial design an experiment in which several independent variables or predictors have been measured; some measured with different entities and others measured with the same entities Factorial ANOV

Mixed-Methods-Designs - eLearning - Methoden der

Mixed Research Design. Mixed research design refers to a research design which encompasses the methods of both qualitative and quantitative research methods or models. Types of Mixed Research Designs. Mixed Method Research; Mixed Model Research; 1) Quantitative Research Methods A) Experimental Designs. True Experimental Design ; Double-Blind Experiment Design of Experiments (DOE) techniques enable designers to determine simultaneously the individual and interactive effects of many factors that could affect the output results in any design. DOE also provides a full insight of interaction between design elements; therefore, helping turn any standard design into a robust one. Simply put, DOE helps to pin point the sensitive parts and sensitive. Matched Pairs Design. Where participants take part in only one experimental condition, but they are recruited specifically to be similar in relevant characteristics (e.g. intelligence, gender, age) to 'matched' participants in the other condition(s). Strengths. Order effects will not be observed as participants only take part in one condition In zweifaktoriellen Designs kann also neben den beiden Haupteffekten (A) + (B) auch ein Interaktionseffekt (A*B) auftreten. Haupteffekte lassen sich grafisch in Diagrammen veranschaulichen (siehe Beispiele unten). So sieht man auf einen Blick, wie sie gewirkt haben. Hierfür werden die Mittelwerte unter der jeweiligen Bedingung (A1, A2 An) und (B1, B2Bn) in ein Diagramm eingezeichnet.

COVID-19 is proving the wisdom of healthcare design - what

mixed methods designs are found in mixed methods studies where the use of mixed methods arises due to issues that develop during the process of conducting the research. Emergent mixed methods designs generally occur when a second approach (quantitative or qualitative) is added after the study is underway because one method is found to be inadequat Design of experiments (DOE) is defined as a branch of applied statistics that deals with planning, conducting, analyzing, and interpreting controlled tests to evaluate the factors that control the value of a parameter or group of parameters Design of Experiments (DOE) is also referred to as Designed Experiments or Experimental Design - all of the terms have the same meaning. Experimental design can be used at the point of greatest leverage to reduce design costs by speeding up the design process, reducing late engineering design changes, and reducing product material and labor complexity 10 October 2020 Design and experiment of C 4 F 7 N/CO 2 mixed gas portable detection system based on NDIR technology. Xiantian Li, Shukai He, Xianzhong Wang, Xiaozhe Zeng, Xinmei Hou, Qianqian Wu, Jingwei Li, Hui Zhu. Author Affiliations + Proceedings Volume 11554. Of course, complete perfection in an experiment is almost impossible, because time, resources and unknown factors will always play a significant role. The main point is that the experimental design should strive towards this goal. The Design of Experiment is also influenced by the specific field of science. Physical sciences rarely have to consider ethics or random fluctuations; one lump of iron, for a chemistry experiment, is usually similar to another. Children, by contrast not only vary.

Mixed Designs - Discovering Statistic

  1. We present a novel mixed methods design, the qualitative vignette experiment, defined as the use of vignettes designed to introduce experimentally controlled variation in information within qualitative semistructured interviews. We argue that this design can provide context-rich data on causal mechanisms. This article contributes to the debate.
  2. ary considerations: - Consider your philosophy and theor
  3. e if a mixed methods study is 'feasible' Step 2:- Identify a rationale for mixing methods Step 3:- Identify a data collection strategy Step 4:- Develop Quant., Qual. & Mixed methods Questions Step 5:- Collect Quant. & Qual. Data Step 6:- Analyze data separately, concurrently, or both Step 7:-Write the 'report' as a one or two-phase or a multiple phase study 6/7/2017manandharnetra999@gmail.com 2
  4. Experimental design refers to how participants are allocated to the different groups in an experiment. Types of design include repeated measures, independent groups, and matched pairs designs. Probably the commonest way to design an experiment in psychology is to divide the participants into two groups, the experimental group, and the control group, and then introduce a change to the.
  5. Designing experiments involves a marriage of biological and mathematical sciences. The mathematical, or statistical, science is obvious. We use scientific fundamentals and principles that have been developed during the past century to conduct three types of experiments. Observational experiments are those designed to measure or verify an assumed constant, such as the velocity of light or the.
  6. Mixed‐effects models offer a powerful framework to do so. Nested effects can usually be fitted using the syntax for crossed effects in mixed models, provided that the coding reflects implicit nesting. But the experimental design (either nested or crossed) affects the interpretation of the results

Mixed-Methods richtig in deiner Abschlussarbeit anwende

Is this a mixed design experiment?! : psychologyresearc

Experimental design has in turn become more challenging, as experiments must conform to an ever-increasing diversity of design constraints. In this article we demonstrate how this design process can be greatly assisted using an optimization tool known as Mixed Integer Linear Programming (MILP). MILP provides a rich framework for incorporating many types of real-world design constraints into a. However, not all experiments can use a within-subjects design nor would it be desirable to. Carryover Effects and Counterbalancing. The primary disad vantage of within-subjects designs is that they can result in carryover effects. A carryover effect is an effect of being tested in one condition on participants' behaviour in later conditions. One type of carryover effect is a practice effect.

Uses of Mixed Methods Research Designs. Mixed methods can be an ideal technique to assess complex interventions such as PCMHs (Homer, Klatka, Romm, et al., 2008; Nutting, Miller, Crabtree, et al., 2009). PCMH evaluators can choose from five primary mixed methods designs depending on the research questions they want to answer and resources available for the evaluation. Validate findings using. This method of concrete mix design or proportioning mainly is based on the extensive field and laboratory experiments carried out by Road Research laboratory U.K. The Road Note 4 method was published for the first time in 1950. This method of mix design was most popular and widely used upto 1970 all over the world. Most of the Indian Concrete roads and air fields were designed by this method. Experimental Design: Multiple Independent Variables Characteristics of Factorial Designs Possible Outcomes of a 2 X 2 Factorial Experiment Different Types of Factorial Designs Completely randomized (independent samples) Repeated measures Mixed design Interpreting Main Effects and Interactions More Complex Factorial Designs Case Analysis General Summary Detailed Summary Key Terms Review.

Though materials designs are used as examples, the method presented is generic and can be utilized for other mixed variable design optimization problems that involve expensive physics-based. • In an embedded design, conducting initial qualitative interviews to build an intervention before an experiment may be helpful in designing the intervention. However, using the initial interview data to place to place participants into a control group where they do not receive a beneficial treatment presents an ethical issue. 6. Quality of Inference. Mixed methodologists prefer to use. Mixed Reality Design Labs share experimental samples, explorations and learning from Windows Mixed Reality Design group. If you are looking for official toolkit, please use Mixed Reality Toolkit - microsoft/MixedRealityDesignLabs_Unit

Mixed Methods Research Designs Research Rundown

This type of experimental design can be advantageous in some cases, but there are some potential drawbacks to consider. A major drawback of using a within-subject design is that the sheer act of having participants take part in one condition can impact the performance or behavior on all other conditions, a problem known as a carryover effect.   So for instance in our earlier example. Learn about experimental designs, completely randomized designs, randomized block designs, blocking variables, and the matched pairs design.If you found this..

Einstieg in die mixed ANOVA - StatistikGur

  1. e whether any change in back pain (i.e., the dependent variable) is the result of the interaction between the type of treatment (i.e., the massage programme or acupuncture programme; that is, the conditions, which is the between-subjects factor) and time (i.e., the within-subjects factor, consisting of three time.
  2. Experimental Design (can use quasi-experimental design) Correlational Design collect qual collect qual Correlational Experimental Explanatory design Between-subjects-pre- and posttest design Predictive design Within-subjects-cross-over design-factorial design. 43 The Embedded Design The researcher: Collects and analyzes quantitative and qualitative data within a quantitative research design.
  3. Mixed methodology research incorporates both qualitative and quantitative research methods. Qualitative research methods provide detailed descriptions about phenomena and may include interviews, observations, and analyses of documents, records, artifacts, photos, and film. Researchers choose this methodology when they are interested in a rich narrative description with an abundance of deep detail
  4. The design of asphalt paving mix, as with the design of other engineering materials is largely a matter of selecting and proportioning constituent materials to obtain the desired properties in the finished pavement structure.The desirable properties of Asphalt mixes are:1. Resistance to permanent deformation: The mix should not distort or be displaced when subjected to traffic loads. The.
  5. • Design of experiments is often presented as a one‐shot approach Build the experiment according to your run budget Perform the experiment Analyze data, optimize, and go home • This is often wasteful in my experience. Crash Course in Mixture DOE 3

The design space of a mixture experiment is the set of possible combinations of the relative proportion of each component, which usually add up to a certain value. Exploring design space means evaluating the various design options possible with a given technology and optimizing with respect to specific constraints, such as process or amount. Figure 1 illustrates the distinction between factorial design space and mixture design space for three different components Experimental design has in turn become more challenging, as experiments must conform to an ever-increasing diversity of design constraints. In this article we demonstrate how this design process can be greatly assisted using an optimization tool known as Mixed Integer Linear Programming (MILP). MILP provides a rich framework for incorporating many types of real-world design constraints into a neuroimaging experiment. We introduce the mathematical foundations of MILP, compare MILP. Our proposed Bayesian Optimization framework for data-driven materials design consists four major steps (as shown in Fig. 1): (1) Step 1 involves creating a materials dataset (either physical or. Chapter 9 Three-Level and Mixed-Level Factorial and Fractional Factorial Designs.. 173 Example 9.1 The 33 Design Designing experiments with specialized design of experiments (DOE) software is more efficient, complete, insightful, and less error‐prone than producing the same design by hand with tables. In addition, it provides the ability to generate algorithmic designs (according to.

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Mehrfaktorielle Versuchspläne - eLearning - Methoden der

Using the data frame below, I managed to compute a repeated-measures ANOVA for subject reaction time. Here is the data frame in question: > str(a) 'data.frame': 2778 obs. of 9 variables: $.. Design of Experiments (DOE) is statistical tool deployed in various types of system, process and product design, development and optimization. It is multipurpose tool that can be used in various situations such as design for comparisons, variable screening, transfer function identification, optimization and robust design. This paper explores historical aspects of DOE and provide within-subject-design: dieselbe Person absolviert nacheinander alle experimentellen Bedingungen (oft bei allgemeinpsychologischen Experimenten) between-subject-design: jede Person wird nur einer Stufe der unabhängigen Variable zugeordnet

Mixed Level Designs Mixed Design Experiments Quality

The package currently includes functions for creating designs for any number of factors: Factorial Designs. General Full-Factorial (fullfact) 2-Level Full-Factorial (ff2n) 2-Level Fractional-Factorial (fracfact) Plackett-Burman (pbdesign) Response-Surface Designs. Box-Behnken (bbdesign) Central-Composite (ccdesign) Randomized Designs. Latin-Hypercube (lhs ACI Mix Design The most common method used in North America is that established by ACI Recommended Practice 211.1 Any mix design procedure will provide a first approximation of the proportions and must be checked by trial batches. Local characteristics in materials should be considered. The following sequence of steps should be followed: (1) determine the job parameters - aggregate properties. The design method in this research is established by using Genetic Algorithm (GA) and the MCNP Code. The parameters, such as the thickness, density and components of shielding material, are set in cell cards and material cards in MCNP code. The data showing the dose equivalent of neutrons and γ rays are extracted from the output file of the MCNP code, which are then set as the objective function of GA. In the GA program, the optimal combination of structure, components and. Question: Designing A Mixed Design 2 X 2 Experiment. This problem has been solved! See the answer. Designing a mixed design 2 x 2 experiment. Expert Answer 100% (1 rating) A mixed factorial design involves two or more independent variables, of which at least one is a within-subjects (repeated measures) view the full answer. Previous question Next question. Design of Experiments (DOE) with JMP ® Design of experiments, or DOE, is a practical and ubiquitous approach for exploring multifactor opportunity spaces, and JMP offers world-class capabilities for design and analysis in a form you can easily use. Methodical experimentation has many applications for efficient and effective information gathering. To reveal or model relationships between an input, or factor, and an output, or response, the best approach is to deliberately change the former.

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• Differentiate these approaches based upon:-Philosophical assumptions -Paradigm stances -Interpretive theory, framework or lens of the researcher Objectives (continued)• Describe the research process:- Definition of Mixed Methods Research• A researcher who uses mixed methods research is using a research design with philosophical assumptions as well as methods of inquiry. • As a methodology, it involves philosophical assumptions that guide the direction of collecting, analyzing. In a quasi-experiment, at least one independent variable is not manipulated, and there is no random assignment to conditions. A mixed method is simply one which uses both between-subjects and. For many experimental psychologists, the go-to methodological designs are cross-sectional. Cross-sectional studies involve measuring the relationship between some variable(s) of interest at one point in time; some common examples include single-session lab studies and online surveys (e.g., via MTurk). These designs can be useful for isolating relationships between variables, establishin experimental approaches: 1) matching, 2) mixed designs, 3) single-subject designs, and 4) developmental designs. The major threats to quasi-experimental designs are confounding variables: variables other than the independent variable that (a) tend to co-vary with the independent variable and (b) are plausible causes of the dependent variable. Quasi-experiments are designed to reduce.

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Mixed Factorial Design Some Variables can be Repeated Measured while others are between groups The difficult part is knowing which term is correct for the F ratio. Computer program may do the analysis for you, but you need to know which variables are within versus between Several Variations on this design MANOVA, ANCOVA. MANOVA Suppose in the ―Charity‖ study we had several dependent. MARSHALL METHOD OF MIX DESIGNIn this method, the resistance to plastic deformation of a compacted cylindrical specimen of bituminous mixture is measured when the specimen is loaded diametrically at a deformation rate of 50 mm per minute. There are two major features of the Marshall method of mix design. (i) density-voids analysis and (ii) stability-flow tests. The Marshall stability of the mix is defined as the maximum load carried by the specimen at a standard test temperature of 60°C. The. Quantitative research methods, on the other hand, include randomized experimental and quasi-experimental designs, surveys, written or oral assessments, and other standardized instruments with which responses can be measured on a numerical scale. Statistical procedures are then used to analyze the numerical responses. In mixed methods research, both qualitative and quantitative methods are used in data collection or data analysis in the same study. Mixed methodologists believe that this. Standards for Mix design ACI and other standards only serves as a guide, initial designs must be confirmed by laboratory trial and plant trial, adjustments on the design shall be done during trial mixes. Initial design on paper is never the final design. 2. Trial Mixes Always carry out trial mixes using the materials for actual use 3. Design Variation Tests Carry out 2 or 3 design variations for every design target 4. Safety Factors Consider always the factor of safety, (1.

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