scholarly journals Assessing the Effect of Laboratory Activities on Core Curricular Units of an Engineering Master’s Program: A Multivariate Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
António M. Lopes ◽  
Lucas da Silva ◽  
Jorge Seabra
Keyword(s):  
Multivariate Analysis ◽  
Multidimensional Scaling ◽  
Statistical Methods ◽  
Mechanical Engineering ◽  
Dimensional Space ◽  
Master's Program ◽  
Performance Indices ◽  
Computer Visualization ◽  
Laboratory Activities

This paper studies the effect of laboratory activities on the results obtained by the students on 7 core curricular units (CUs) of an Integrated Master in Mechanical Engineering. Each CU is characterized by means of 4 performance indices, over the 6-year period 2014/2015–2019/2020. Firstly, individual indices in a per semester basis are compared. Secondly, the CUs are regarded as objects defined in a 4-dimensional space of features, and the multidimensional scaling (MDS) technique is adopted for clustering and computer visualization. The MDS is powerful for analyzing the multivariate dataset, unveiling patterns not perceived by standard statistical methods.

MULTIVARIATE ANALYSIS OF PERCEIVED DYSFUNCTION RATINGS OF PERSONALITY DISORDER SYMPTOMS

2004 ◽  
Vol 32 (6) ◽  
pp. 595-606
Author(s):  
David C. Watson ◽  
Andrew J. Howell
Keyword(s):  
Factor Analysis ◽  
Multivariate Analysis ◽  
Personality Disorder ◽  
Multidimensional Scaling ◽  
Personality Disorders ◽  
Two Dimensions ◽  
Social Impairment ◽  
Multivariate Techniques ◽  
Personal Distress ◽  
High Distress

Dysfunction in personality disorder symptoms was assessed using multivariate techniques to analyse lay judges' (N = 216) ratings of occupational impairment, social impairment, and personal distress. Factor analysis revealed that ratings of occupational impairment and social impairment loaded onto distinct factors. Personal distress ratings loaded onto two separate factors: high distress and low distress. Multidimensional scaling revealed two dimensions for overall dysfunction among personality disorders: severity of dysfunction and internalization-externalization. The dimensions were independence-dependence and severity of dysfunction for occupational impairment, interpersonal involvement and dominance-submission for social impairment, and internalization-externalization and severity for personal distress.

scholarly journals GENETIC ALGORITHMS FOR MULTIDIMENSIONAL SCALING / GENETINIŲ ALGORITMŲ TAIKYMAS DAUGIAMATĖMS SKALĖMS

2015 ◽  
Vol 7 (3) ◽  
pp. 275-279 ◽  
Author(s):  
Agnė Dzidolikaitė
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Multidimensional Scaling ◽  
Optimization Problem ◽  
Dimensional Space ◽  
Local Solution ◽  
Multidimensional Data ◽  
Global Optimization Problem ◽  
Lower Dimensional Space ◽  
Lower Dimensional

The paper analyzes global optimization problem. In order to solve this problem multidimensional scaling algorithm is combined with genetic algorithm. Using multidimensional scaling we search for multidimensional data projections in a lower-dimensional space and try to keep dissimilarities of the set that we analyze. Using genetic algorithms we can get more than one local solution, but the whole population of optimal points. Different optimal points give different images. Looking at several multidimensional data images an expert can notice some qualities of given multidimensional data. In the paper genetic algorithm is applied for multidimensional scaling and glass data is visualized, and certain qualities are noticed. Analizuojamas globaliojo optimizavimo uždavinys. Jis apibrėžiamas kaip netiesinės tolydžiųjų kintamųjų tikslo funkcijos optimizavimas leistinojoje srityje. Optimizuojant taikomi įvairūs algoritmai. Paprastai taikant tikslius algoritmus randamas tikslus sprendinys, tačiau tai gali trukti labai ilgai. Dažnai norima gauti gerą sprendinį per priimtiną laiko tarpą. Tokiu atveju galimi kiti – euristiniai, algoritmai, kitaip dar vadinami euristikomis. Viena iš euristikų yra genetiniai algoritmai, kopijuojantys gyvojoje gamtoje vykstančią evoliuciją. Sudarant algoritmus naudojami evoliuciniai operatoriai: paveldimumas, mutacija, selekcija ir rekombinacija. Taikant genetinius algoritmus galima rasti pakankamai gerus sprendinius tų uždavinių, kuriems nėra tikslių algoritmų. Genetiniai algoritmai taip pat taikytini vizualizuojant duomenis daugiamačių skalių metodu. Taikant daugiamates skales ieškoma daugiamačių duomenų projekcijų mažesnio skaičiaus matmenų erdvėje siekiant išsaugoti analizuojamos aibės panašumus arba skirtingumus. Taikant genetinius algoritmus gaunamas ne vienas lokalusis sprendinys, o visa optimumų populiacija. Skirtingi optimumai atitinka skirtingus vaizdus. Matydamas kelis daugiamačių duomenų variantus, ekspertas gali įžvelgti daugiau daugiamačių duomenų savybių. Straipsnyje genetinis algoritmas pritaikytas daugiamatėms skalėms. Parodoma, kad daugiamačių skalių algoritmą galima kombinuoti su genetiniu algoritmu ir panaudoti daugiamačiams duomenims vizualizuoti.

Investigating the Circumplex Structure of the Portrait Values Questionnaire (PVQ)

2005 ◽  
Vol 26 (4) ◽  
pp. 185-193 ◽  
Author(s):  
Andreas Hinz ◽  
Elmar Brähler ◽  
Peter Schmidt ◽  
Cornelia Albani
Keyword(s):  
Multidimensional Scaling ◽  
Statistical Methods ◽  
Empirical Data ◽  
Representative Sample ◽  
Factorial Analysis ◽  
Dimensional Structure ◽  
Statistical Techniques ◽  
German Population ◽  
Two Dimensional ◽  
Varimax Rotation

Abstract. The Portrait Values Questionnaire (PVQ) comprises 10 basic values that guide behavior. The Schwartz model postulates that these 10 values build a circumplex structure. We examined the PVQ with respect to its dimensional structure using a representative sample (N = 1896) of the German population. The results of three widely used analyses were compared: multidimensional scaling, factorial analysis (with varimax rotation) of raw scores, and factorial analysis with ipsative values. Furthermore, rank correlations between the theoretically assumed circular distances and the empirical data were calculated. The analyses confirmed that the 10 dimensions of the PVQ can be depicted in a two-dimensional plane. However, the statistical techniques chosen yielded different arrangements of the 10 values in the plane. All statistical methods failed to confirm the circumplex structure postulated by Schwartz. Nevertheless, dimensions of higher order that condense the 10 dimensions can be derived for applications of the PVQ.

scholarly journals Tonal Proximity Relationship in the Spanish of the Canary Islands in the Light of Dialectometry

Languages ◽  
2019 ◽  
Vol 4 (2) ◽  
pp. 29
Author(s):  
Josefa Dorta ◽  
María González Rodríguez
Keyword(s):  
Multivariate Analysis ◽  
Multidimensional Scaling ◽  
Canary Islands ◽  
Romance Languages ◽  
International Project ◽  
Scaling Technique ◽  
Research Outcomes

Traditional linguistic geography has not dealt with issues relating to the prosodic study of languages and linguistic varieties. The international project AMPER (Atlas Multimédia Prosodique de l’Espace Roman) achieves a key milestone in this area by studying the prosody of Romance languages and varieties in order to disseminate research outcomes in the form of interactive online atlases. Using prosodic data from a wide corpus of declarative and interrogative sentences, obtained from a range of informants from the seven Canary Islands (AMPERCan), a dialectometric study was carried out with a tool especially designed within the framework of AMPER. Correlation values, dendrograms as well as multivariate analysis by means of the multidimensional scaling technique (MDS), have enabled us to establish relationships of close prosodic proximity among the Canary Islands.

Visualization of Linear Ordering Results for Ordinal Data with Application of Multidimensional Scaling

2017 ◽  
Vol 64 (1) ◽  
pp. 5-20
Author(s):  
Marek Walesiak
Keyword(s):  
Multidimensional Scaling ◽  
Ordinal Data ◽  
Euclidean Distance ◽  
Dimensional Space ◽  
Linear Ordering ◽  
Two Dimensional ◽  
Ideal Object ◽  
Step Procedure

A two-step procedure was proposed to visualization of linear ordering results for ordinal data. In the first step as a result of the application of multidimensional scaling (see Borg, Groenen, 2005; Mair et al., 2016) is to visualize objects in two-dimensional space. In the next step, a linear ordering is carried out with the use of the Euclidean distance from the pattern (ideal) object. The proposed approach expanded the possibilities of interpretation of the results of the linear ordering of set of objects. The article uses the concept of isoquant and path of development (the shortest way connecting ideal and anti-ideal object) proposed by Hellwig (1981). The proposed approach is illustrated by an empirical example with application of script of R environment.

Assessment of gminas’ socio-economic development in the Mazowieckie Voivodship using methods of multivariate analysis

2016 ◽  
Vol 61 (6) ◽  
pp. 59-69 ◽  
Author(s):  
Mariola Chrzanowska ◽  
Nina Drejerska
Keyword(s):  
Economic Development ◽  
Multivariate Analysis ◽  
Data Analysis ◽  
Comparative Analysis ◽  
Statistical Methods ◽  
Local Development ◽  
Relative Level ◽  
Development Level ◽  
Socio Economic Development ◽  
Quantitative Characteristics

Statistical methods for comparing objects allow them to study taking into account several features simultaneously, thereby increasing the efficiency of testing. It can be concluded that the methods of multidimensional comparative data analysis can provide specific research instruments of local development. The article presents the proposal to apply to study the level of development of gminas in the Mazowieckie Voivodship two methods of multidimensional comparative analysis, ie. indicator of the relative level of development as well as a synthetic measure which takes into account the zero unitarisation method. The assessment of the development level of gminas was carried out using quantitative characteristics based on data from the official statistics for the years 2007 and 2013.

scholarly journals The use of Statistical Methods in Mechanical Engineering

2013 ◽  
Vol 5 (7) ◽  
pp. 2327-2331 ◽  
Author(s):  
Iram Saleem ◽  
Muhammad Aslam ◽  
Muhammad Azam
Keyword(s):  
Statistical Methods ◽  
Mechanical Engineering

scholarly journals Analysis of Forest Fires by means of Pseudo Phase Plane and Multidimensional Scaling Methods

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
J. A. Tenreiro Machado ◽  
António M. Lopes
Keyword(s):  
Time Series ◽  
Multidimensional Scaling ◽  
Forest Fires ◽  
Phase Plane ◽  
Dimensional Space ◽  
Second Phase ◽  
Burnt Area ◽  
Long Range Correlations ◽  
Scaling Methods ◽  
Pseudo Phase Plane

Forest fires dynamics is often characterized by the absence of a characteristic length-scale, long range correlations in space and time, and long memory, which are features also associated with fractional order systems. In this paper a public domain forest fires catalogue, containing information of events for Portugal, covering the period from 1980 up to 2012, is tackled. The events are modelled as time series of Dirac impulses with amplitude proportional to the burnt area. The time series are viewed as the system output and are interpreted as a manifestation of the system dynamics. In the first phase we use the pseudo phase plane (PPP) technique to describe forest fires dynamics. In the second phase we use multidimensional scaling (MDS) visualization tools. The PPP allows the representation of forest fires dynamics in two-dimensional space, by taking time series representative of the phenomena. The MDS approach generates maps where objects that are perceived to be similar to each other are placed on the map forming clusters. The results are analysed in order to extract relationships among the data and to better understand forest fires behaviour.

Multivariate Analysis: The Need for Data, and other Problems

1975 ◽  
Vol 126 (3) ◽  
pp. 237-240 ◽  
Author(s):  
B. S. Everitt
Keyword(s):  
Multivariate Analysis ◽  
Statistical Methods ◽  
Multivariate Analyses ◽  
Careful Consideration ◽  
Initial Screening ◽  
Journal Editors ◽  
Variable Distribution ◽  
Significance Levels ◽  
Type Variable ◽  
Size Variable

SummaryMultivariate analyses are an aid to, not a substitute for critical thinking in the area of data analysis. Meaningful results can only be produced by these methods if careful consideration is given to questions of sample size, variable type, variable distribution etc., and accusations of subjectivity in interpretation can only be overcome by replication.The computer revolution has produced many problems for statisticians, not least of which is the ease with which experimenters may access packages of programs for multivariate analysis, and so bypass a ‘difficult’ (by which is meant one who will not do simply as he is told) statistician. Of course there are many abuses of univariate statistical methods. Here, however, the abuses are not likely to lead to such seriously misleading results as in the multivariate case.Perhaps a major cause of the continuing misuse of statistical methods is the insistence of many journal editors in psychology and related areas, on articles being laced with multivariate analyses, and on encouraging the pedantic use of significance levels, i.e. the inevitable p < —, as if such inclusions lent an air of respectability to their journal which it might not otherwise have had. Research workers in these fields would be better encouraged to devote more time to an initial screening of their data using simple graphical techniques, to ensure that their data are at least approximately suitable for more complicated multivariate analyses.

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