Statistics for Engineering and the Sciences

Mendenhall, William M.; Sincich, Terry

doi:10.1201/b19628

Cited by 138 publications

(134 citation statements)

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“…From a statistical point of view, the basis for this article is using a formula for the function of the multiple-linear regression. This research follows function according (Mendenhall, 2016, López-Espín, 2012…”

Section: Methodsmentioning

confidence: 99%

Quantified impact of market interest rates on commercial banks’ business mix

Kostikov¹,

Jílková²,

Stránská³

2019

Journal of International Studies

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The main aim of this paper is to measure the influence of market interest rate on commercial banks' business mix. The global character of banking business and the conditions of the world economy have caused extremely low interest rates at the loan and mortgage market in Czech Republic. Low interest rates generate cheaper money and make loans and mortgages easily available since 2014 where the mortgage interest rate dropped below the level of 2.5%. The first aim of this research is to evaluate the effect from different types of interest rates on two types of loan products in this five-year period (2014-2018). The second aim of this research is to analyse the effect from the selected interest rates in Czech Republic on profitability of the selected commercial banks. Lastly, profitability behaviour of the banking sector in Czech Republic and its relation with the selected interest rates and bank-specific determinants has been examined. Our final results state that the consumption interest rate, mortgage interest rate, deposit interest rate, PRIBOR 2w-repo, inflation rate, disposable income, unemployment, GDP and the real effective exchange rate (REER) have significant influence on the volume of mortgage loans and consumer loans too. The authors find that banks´ ROE is affected by profit margin and liquidity, but it is negatively related to financial leverage and the

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Section: Methodsmentioning

confidence: 99%

Quantified impact of market interest rates on commercial banks’ business mix

Kostikov¹,

Jílková²,

Stránská³

2019

Journal of International Studies

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“…68% of all measurements; two standard deviations would be c . 95%, and for three, 99.7% . Figure reflects that the chosen curving fitting extrapolates that file lengths beyond 30 min will probably produce no meaningful reduction in the SD values. Based on the audio file formats, the average SD values were in the following order from lowest to highest: WMA (SHQ to STXQ recording modes), PCM, WMA (LP to HQ), MP3 (128–256 kilobytes per second [kbps]), MP3 (8–64 kbps), ADPCM, and DSS (see Table ). The DSS results were appreciably higher than the other formats.…”

Section: Results and Conclusionmentioning

confidence: 99%

The Average Direct Current Offset Values for Small Digital Audio Recorders in an Acoustically Consistent Environment

Koenig¹,

Lacey²

2014

Journal of Forensic Sciences

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In this research project, nine small digital audio recorders were tested using five sets of 30-min recordings at all available recording modes, with consistent audio material, identical source and microphone locations, and identical acoustic environments. The averaged direct current (DC) offset values and standard deviations were measured for 30-sec and 1-, 2-, 3-, 6-, 10-, 15-, and 30-min segments. The research found an inverse association between segment lengths and the standard deviation values and that lengths beyond 30 min may not meaningfully reduce the standard deviation values. This research supports previous studies indicating that measured averaged DC offsets should only be used for exclusionary purposes in authenticity analyses and exhibit consistent values when the general acoustic environment and microphone/recorder configurations were held constant. Measured average DC offset values from exemplar recorders may not be directly comparable to those of submitted digital audio recordings without exactly duplicating the acoustic environment and microphone/recorder configurations.

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“…If A=58 is the total number of available samples and T=28 is the number of treated ones, given a binary variable or node, it is counted the number of samples that exhibits a particular variable level (value of 0 or of 1), say a, and how many of these samples are treated, say t. Then the following probabilistic calculation 10 gives the probability to encounter t or more treated samples if a≥t are randomly selected…”

mentioning

confidence: 99%

Analyzing chromatographic data with the Superposing Significant Interaction Rules (SSIR) chemometric tool

Besalú

Prat²,

Anticó

2020

Proceedings of MOL2NET 2020, International Conference on Multidisciplinary Sciences, 6th Edition

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This study describes a new chemometric tool for the analysis of chromatographic data: the Superposing Significant Interaction Rules (SSIR) is a variable selector coming from QSAR field that directly analyses the raw internal data coming from the chromatographic software. This allowed the identification of relevant volatile compounds in cork (treated and not treated samples in the industry) extracted by untargeted HS-SPME in a particular case for which traditional treatments (PCA, Discriminant Analysis) did not produced relevant results. The procedure has revealed the presence of compounds which are increased in the case of treated samples. The obtained classificatory model is robust, as it passed satisfactorily cross-validation tests (96% or more in performance for leave-one-out processes). This is the first time SSIR procedure is applied for the analysis of chromatographic information.

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Statistics for Engineering and the Sciences

Cited by 138 publications

References 0 publications

Quantified impact of market interest rates on commercial banks’ business mix

Quantified impact of market interest rates on commercial banks’ business mix

The Average Direct Current Offset Values for Small Digital Audio Recorders in an Acoustically Consistent Environment

Analyzing chromatographic data with the Superposing Significant Interaction Rules (SSIR) chemometric tool

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