An Empirical Analysis on Outlier Detection of Land Real Price using Nonparametric Statistical Test

2021 ◽  
Vol 23 (3) ◽  
pp. 43-55
Author(s):  
So Yoon Lee ◽  
Gyo Eon Shim
Keyword(s):  
Outlier Detection ◽  
Empirical Analysis ◽  
Statistical Test ◽  
Real Price ◽  
Nonparametric Statistical Test ◽  
Nonparametric Statistical

ANOCVA: A Nonparametric Statistical Test to Compare Clustering Structures

2018 ◽  
pp. 113-125
Author(s):  
Alexandre Galvão Patriota ◽  
Maciel Calebe Vidal ◽  
Davi Augusto Caetano de Jesus ◽  
André Fujita
Keyword(s):  
Statistical Test ◽  
Nonparametric Statistical Test ◽  
Nonparametric Statistical

scholarly journals Big Data Characterization of Learner Behaviour in a Highly Technical MOOC Engineering Course

2016 ◽  
Vol 3 (3) ◽  
pp. 170-192 ◽  
Author(s):  
Kerrie Anna Douglas ◽  
Peter Bermel ◽  
Md Monzurul Alam ◽  
Krishna Madhavan
Keyword(s):  
Big Data ◽  
Learning Analytics ◽  
Statistical Test ◽  
Future Research ◽  
User Behaviour ◽  
Significant Difference ◽  
Nonparametric Statistical Test ◽  
Nonparametric Statistical

MOOCs attract a large number of users with unknown diversity in terms of motivation, ability, and goals. To understand more about learners in a MOOC, the authors explored clusters of user clickstream patterns in a highly technical MOOC, Nanophotonic Modelling through the algorithm k-means++.  Five clusters of user behaviour emerged: Fully Engaged, Consistent Viewers, One-Week Engaged, Two-Week Engaged, and Sporadic users. Assessment behaviours and scores are then examined within each cluster, and found different between clusters. Nonparametric statistical test, Kruskal-Wallis yielded a significant difference between user behaviour in each cluster. To make accurate inferences about what occurs in a MOOC, a first step is to understand the patterns of user behaviour. The latent characteristics that contribute to user behaviour must be explored in future research. Keywords: MOOCs, Learning Analytics, Assessment

scholarly journals Nonparametric flow cytometry analysis.

1979 ◽  
Vol 27 (1) ◽  
pp. 293-296 ◽  
Author(s):  
C B Bagwell ◽  
J L Hudson ◽  
G L Irvin
Keyword(s):  
Flow Cytometry ◽  
Statistical Method ◽  
Biological Systems ◽  
Bayes Theorem ◽  
Statistical Test ◽  
Flow Cytometry Analysis ◽  
Nonparametric Statistical Test ◽  
The Mean ◽  
Nonparametric Statistical

A nonparametric statistical test for the analysis of flow cytometry derived histograms is presented. The method involves smoothing and translocation of data, area normalization, channel by channel determination of the mean and S.D., and use of Bayes' theorem for unknown histogram classification. With this statistical method, different sets of histograms from numerous biological systems can be compared.

scholarly journals NONPARAMETRIC STATISTICAL TEST APPROACHES IN GENETICS DATA

2015 ◽  
Vol 5 (1) ◽  
pp. 77 ◽  
Author(s):  
RAKESH Kumar Saroj ◽  
K.H.H.V.S.S. Narsimha Murthy ◽  
Mukesh Kumar
Keyword(s):  
Statistical Test ◽  
Nonparametric Statistical Test ◽  
Nonparametric Statistical

scholarly journals A Pilot Study for the Statistical Treatment of Nutritional Parameters in the Quality Control of Canned Fishing Goods

1999 ◽  
Vol 82 (5) ◽  
pp. 1247-1256
Author(s):  
Marta Bartos-Lorenzo ◽  
Alberto Calviño-López ◽  
Fernando Dalama-Iglesias ◽  
Maria de la Torre-Lamosa ◽  
Guadalupe Martín-Pardo ◽  
...  
Keyword(s):  
Pilot Study ◽  
Statistical Treatment ◽  
Statistical Test ◽  
Nutritional Composition ◽  
Data Sets ◽  
Total Proteins ◽  
European Directives ◽  
Nonparametric Statistical Test ◽  
Chemometric Techniques ◽  
Nonparametric Statistical

Abstract This pilot study was derived as a consequence of European Directives 496/90 and 493/91 in which a regulation on the labeling of canned fishing goods was established. The study was intended primarily to assess whether different Spanish canned fishing goods might be differentiated by their basic nutritional composition (i.e., ash, chlorine as NaCl, fat, humidity, total proteins, and dry residue) and, second, to study each particular type of good. Accordingly, a univariate nonparametric statistical test and 2 multivariate chemometric techniques (factor and cluster analyses) were used. The pilot study revealed that (1) the basic nutritional variables did not allow a clear distinction among canned goods when different commodities were considered, but they seemed useful for obtaining information for only one type of good; and (2) the variables that gave the most useful information to visualize the appearance of groups in the data sets were humidity, dry residue, fat, and proteins, although their particular usefulness was found to be different when different species were considered.

scholarly journals COMBINED NONPARAMETRIC CHI-SQUARED AND BINOMIAL STATISTICAL TEST ON TRUCK TRAFFIC VOLUME CHANGES IN CANADIAN PROVINCIAL HIGHWAY NETWORK

Transport ◽  
2019 ◽  
Vol 34 (1) ◽  
pp. 103-114 ◽  
Author(s):  
Hyuk-Jae Roh ◽  
Satish Sharma
Keyword(s):  
Statistical Tests ◽  
Weather Conditions ◽  
Statistical Test ◽  
Truck Traffic ◽  
Long Distance ◽  
Type Distribution ◽  
Weigh In Motion ◽  
Highway Network ◽  
Chi Squared ◽  
Nonparametric Statistical

This paper examines the effect of weather conditions on truck type distribution using combined nonparametric chi-squared and binomial probability statistical tests. Influence of the winter conditions on truck type distribution is investigated in this paper by classifying trucks into single-unit trucks, single-trailer, and multi-trailer units. The investigation is based on 5 years Weigh-In-Motion (WIM) traffic data collected from Alberta provincial highway network in Canada. The WIM data is collected from six WIM sites located on Highway 2, Highway 2A, Highway 3, Highway 16 and Highway 44. The objective of this study is to investigate the association of three truck type distribution with month and season depending on weather conditions by means of nonparametric statistical test. The statistical results indicate that the variation of truck type distribution is influenced by type of highway facility, such as regional commuter roads and rural long distance highways. The season of the year (winter and non-winter) may also affect the truck type distribution on some types of roads. Findings of this study can benefit highway agencies in developing programs and policies related to efficient monitoring of truck traffic and maintaining highway network throughout the year.

scholarly journals Peramalan dan deteksi outlier saham perusahaan angkutan laut umum di masa covid-19 dengan pemodelan arima

2021 ◽  
Vol 3 (1) ◽  
pp. 8
Author(s):  
Ilham Thaib ◽  
Gesit Thabrani ◽  
Silvia Netsyah
Keyword(s):  
Confidence Interval ◽  
Outlier Detection ◽  
Autocorrelation Function ◽  
Stock Price ◽  
Arima Model ◽  
Statistical Test ◽  
P Value ◽  
The Public ◽  
Price Data ◽  
Partial Autocorrelation Function

The public sea freight sector is one of the affected by COVID-19. PT. Samudera Indonesia Tbk is one of the sea transportations companies in Indonesia. The ARIMA model in the previous study provided a statistical test with the aim of evaluating the suitability of the model with a p value of less than 0.05 to determine ARIMA by guessing through ACF (Autocorrelation Function) and PACF (Partial Autocorrelation Function) through stationary data. Outlier detection can be done by plotting the residuals from the specified model. Forecasting data for the next 5 days using the ARIMA (3,1,2) model can be seen that the results of forecasting stock price data for PT. Samudera Indonesia Tbk using ARIMA (3,1,2) is within the 95% confidence interval with a forecast value that is close to the actual value. There are outliers that are detected which are related to economic phenomena.Keywords: Forecasting, Covid-19, stock, ARIMA, outlier

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