Methods of Statistical Research for Information Managers

Kaminskyi, Roman; Kunanets, Nataliia; Rzheuskyi, Antonii; Khudyi, Andrii

doi:10.1109/stc-csit.2018.8526588

Cited by 8 publications

(4 citation statements)

References 1 publication

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“…Handling lost data; Missing Value is the loss of some data that has been obtained. In the world of data science, missing value is closely related to the process of data disputes (data wrangling) before later data analysis and prediction will be carried out [9] [10]. Data wrangling is an activity of uniformizing data or cleaning data (cleaning data) from dirty (raw) data to data that will be ready to be used for analysis.…”

Section: Figure 9 Outlier Value Detection Resultsmentioning

confidence: 99%

Data Science With Excel

Setiyanto¹,

Setiawan²

2022

IJCIS

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The stages in data science consist of several stages, one of which is data preparation. At this stage, many things are done so that the dirty data becomes clean data that is ready for modeling. Many applications offer data science convenience in terms of processing data. One of them is excel, this application from Microsoft can perform data processing so that the data is ready for modeling. However, there are limitations in using excel. The maximum number of rows that excel has is only 1,048,576 and the number of columns is 16,384. However, if you process data of no more than 1 million rows, excel can still handle it by using features such as error detection, removing duplicate data, correcting error values, detecting outlier values, handling missing data and validating data. This study shows some of these features along with examples of their use.

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Section: Figure 9 Outlier Value Detection Resultsmentioning

confidence: 99%

Data Science With Excel

Setiyanto¹,

Setiawan²

2022

IJCIS

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“…The SuperDARN data initially have a time resolution of 2 min, sometimes with data gaps. For further analysis a third-degree polynomial fitting is used to populate the data gaps (Kaminskyi et al, 2018;Van Camp & Vauterin, 2005).…”

Section: 1029/2023ja031367mentioning

confidence: 99%

Simultaneous Occurrence of Traveling Ionospheric Disturbances, Farley Buneman and Gradient Drift Instabilities Observed by the Zhongshan SuperDARN HF Radar

Hiyadutuje,

Habarulema,

Kosch

et al. 2024

JGR Space Physics

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We show that Traveling Ionospheric Disturbances (TIDs) may affect the Farley Buneman Instability (FBI) and Gradient Drift Instability (GDI) echoes referred to as the Near Range Echoes (NREs) in the SuperDARN radar backscatter from the lower part of the E‐region. TIDs and NREs are observed concomitantly by the Zhongshan SuperDARN radar (69.38°S, 76.38°E) in the far and near ranges, respectively. At the moment, there is no study about the effects of TIDs on the NREs caused by the FBI using the SuperDARN radars. The GDI are more likely to occur at a lower altitude while FBI occurs at a slightly higher altitude in the lower part of the ionospheric E‐region. We use the Spearman Correlation Coefficient (SCC) to show that a part of the NREs backscatter power could be statistically explained by the MSTIDs backscatter power received by the same radar. We also investigate the simultaneous occurrence rate of the NREs and MSTIDs during the 24th solar cycle. Seasonal variability shows that MSTIDs‐NREs events over Zhongshan mostly occur in summer and equinoxes during local night and morning. The majority of these events lasted between ∼4 and ∼8 hr. Most events disappeared early in the morning. Statistics of the Spearman correlation coefficient values show that ∼9% of NRE amplitude modulation could be due to the MSTIDs. There are almost equal numbers of negative and positive Spearman correlation coefficient values. The relative velocity between the E‐region NREs and the F‐region MSTIDs switching the electric field polarities between the crests and troughs could be the cause of those equal number of the Spearman correlation coefficient values. The orientation of the ionospheric current relative to the MSTID polarization electric field may also play a significant role in the reported Spearman correlation coefficient values. We argue that in some cases, the TIDs might have been close enough to the NREs altitude to modulate them directly by transporting the plasma up and down through shear or compression.

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“…However, it falls short of discussing intersection of clusters. The algorithms of agglomerative hierarchical clustering and methods for determining similarity between clusters are analyzed in [3]. The objects are presented only on the plane; that is why intersection of clusters is possible too.…”

Section: Related Workmentioning

confidence: 99%