During this trip, and whilst we were recording data, there were problems which were encountered amongst methods, results and therefore the conclusions. The first one we came across was the longshore drift survey part.
Niral Patel 10D 2/12/04 Evaluation: During this trip, and whilst we were recording data, there were problems which were encountered amongst methods, results and therefore the conclusions. The first one we came across was the longshore drift survey part. The cork that was thrown into the sea was lost (poor methodology); therefore the results for this section were inaccurate as the direction/speed of the cork was not known with certainty making the results inaccurate. Because of this, the conclusion would have to be questioned as we are not able to draw a firm or accurate conclusion about the survey on longshore drift. A poor method was when we only received one cork and we were asked to record longshore drift data at two locations. This meant that only one of the two locations would be used, meaning that the results were not accurate overall making the conclusion questionable again for the longshore drift survey section. With the groyne measurements, the most accurate data available was not obtained due to safety reasons, because it would not be safe to climb onto a slippery groyne and take measurements, therefore the most accurate estimates of the groyne measurements were recorded. This was the fault in the method leading to inaccurate results as they were largely based on accurate as
Applied sociological research skills
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Assess the relevance of metaphors to Human - Computer interaction from the perspective of the design
Assess the relevance of metaphors to Human - Computer interaction from the perspective of the design System metaphors appear to be attracting more and more attention and you often hear the term banded about in journals and conference proceedings. The aim of this essay is to examine the potential usefulness of metaphors to the users and designers of systems, concentrating, in particular, on the human-computer interface. It will hopefully be established whether system metaphors are phenomena worthy of serious thought or whether it is simply an empty term with no more than intuitive appeal which will be passed over and forgotten with time. The basic idea behind a metaphor is to understand a new concept in terms of one which is already familiar and understood. A well known metaphor is that of Rutherford's comparison of the hydrogen atom to the solar system. Lakoff and Johnson (1980) see language to be structured metaphorically and claim that this reflects the structure of thought processes in general: Metaphor is pervasive in everyday life, not just in language but in thought and action (Lakoff & Johnson 1980, p3) Many teachers have used metaphor and analogy to facilitate their pupils learning and indeed analogy seems to be a central aspect of learning. Metaphors can be distinguished from models by the partial nature of the correspondence between the old and new concept.
HCI (human-computer interaction).
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Features of Quantitative Research.
Features of Quantitative Research According to Coolican (1990), quantification can be defined as the process of measuring on some numerical basis. Quantitative research tends to be numerical or categorical. This type of research aims to make predictions, establish facts and test hypothesis that have already been stated, that is, aims to find evidence which supports or does not support on existing hypothesis. Quantitative research normally involves large numbers of respondents, typically a hundred or more, and obtains results that are representative of the total population. Therefore, it is a form of research method that is considerably appropriate for generalization of descriptions. There are several main types of approaches to quantitative research (show as following) and these techniques are widely used in many substantive fields to study and explain individual differences and patterns of relationships among variables. > Correlational research aims to find out whether there is a relationship between two or more variables (Gay & Airasian, 1999). In any case, if a relationship is found, then its degree is identified by a number between -1.00 and +1.00 and this number is known as a correlation coefficient. For instance, when one variable increases and the other also increases, then the correlation in this case would be positive. On the other hand, if a correlation is
Was the scientific revolution primarily one concerned with the solar system?
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Hybrid electoral systems the Additional Member System (AMS).
Hybrid electoral systems The Additional Member System (AMS) Introduction Proportional representation is not a voting system but a general term covering a number of systems which deliver seats to a party in proportion to the number of votes it receives. The Additional Member System usually comes under the umbrella of proportional representation as it partly uses a variation of the party list system. The system is really a hybrid of two voting systems which combine to give a proportional result. The Additional Member System was created by the Allies as an electoral system for post-Nazi Germany and was intended to provide stable government. It is a hybrid of the FPTP system and the Party List system. The operation of the AMS system Two key points which characterise the system: . Each voter casts two votes at the same time - one for a constituency MP and the other for a party. 2. There are two different types of MPs elected - constituency MPs and the 'additional members' (those elected using the party lists). The voter casts one vote for a constituency MP. This process is identical to the FPTP system as it operates on a simple majority basis. The candidate with the most votes wins, even if they poll fewer than half of the vote. The second vote is cast for a party; and the voter may wish to vote for a party different from the one supported in
Dimensional Modeling
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A practical using SPSS
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Ethical Decision-Making
Decision Support Systems Sharon Robinson DBM 410 Decision support Systems SPICS1101 University of Phoenix- Clearwater Campus Joe Dobrinski, Jr. May 31, 2005 Workshop #5 Team Assignment Creating a Decision Support System Creating a Decision Support System (DSS) A DSS is an interactive, computer-based system, which has functions for giving a user modeling and data support, which is flexible and adaptable to varying needs in changing environments, with a supportive and easy to use interface, and which has been built to represent the necessary and sufficient problem and knowledge elements of the context it should support (MacDermant, 1998). The ultimate goal of collecting this data is to provide a foundation for business intelligence. Data is drawn from data warehouses, data marts, internal data (generated by business transactions), personal data (individual, subjective estimates, projections, opinions, judgments, etc.), external data (generated outside the organization, but relevant to the organization), economic data (competitive intelligence), and any other data needed for sound decisions. We can collect data manually, by instruments and sensors, scanning, or electronic transfer. The data is transformed into information and knowledge. Data analysis tools are then applied which will augment the decision makers' judgment with facts, analysis, and forecasts. Practical
