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Statistics
Published in Dušan Teodorović, Miloš Nikolić, Quantitative Methods in Transportation, 2020
Dušan Teodorović, Miloš Nikolić
We see that we obtained a standard score for a sample mean by subtracting the mean from our statistic and dividing the result obtained by the standard error. The random variable Z is normally distributed (Figure 5.24), with parameters 0 and 1, i.e. Z~N(0,1). The standard score measures the distance between the sample results and the declared population value, expressed by the number of standard errors.
Statistics for the Safety Professional
Published in W. David Yates, Safety Professional’s Reference and Study Guide, 2020
In statistics, a standard score indicates how many standard deviations an observation or datum is above or below the mean. It is a dimensionless quantity derived by subtracting the population mean from an individual raw score and then dividing the difference by the population standard deviation. This conversion process is called standardizing or normalizing; however, “normalizing” can refer to many types of ratios; see normalization (statistics) for more.
Statistics for the Safety Professional
Published in W. David Yates, Safety Professional’s, 2015
In statistics, a standard score indicates how many standard deviations an observation or datum is above or below the mean. It is a dimensionless quantity derived by subtracting the population mean from an individual raw score and then dividing the difference by the population standard deviation. This conversion process is called standardizing or normalizing; however, “normalizing” can refer to many types of ratios; see normalization (statistics) for more.
Use of joint supervised machine learning algorithms in assessing the geotechnical peculiarities of erodible tropical soils from southeastern Nigeria
Published in Geomechanics and Geoengineering, 2023
The LRA is a kind of regression analysis which is often utilised in establishing the relationship between a binominal (binary) variable and its associated factors. The major difference between the LRA and multiple linear regression is that its response variable is binomial. Just like the simple linear regression, the LRA could also be used to predict a case (Y) with respect to other independent factors (X). In other words, the LRA can also be used to find the association (relationship) between dependent variables, independent variables and predictions, even where the relationship between variables is nonlinear. In the presence of multiple explanatory variables, logistic regression could be used to get the odds and probabilities. Concisely stated, with LRA, estimation of probability and odds could be made precisely. This could still be possible even when the variables are associated with abnormal values (Althuwaynee et al. 2014). In such a scenario, a balance between the continuous and categorical variables can be created through normalisation process. In the standardisation process of a variable, each of its values is transformed to a z-score (i.e. the standard score/measure), which is defined as the variation/difference between the true score and the average score divided by the standard deviation (Nayebi 2020). In some software, like the SPSS, the normalisation process is automatic with the ‘Standardize Command’.
A Study on the Countermeasures to Improve the Physical and Mental Health of High-Altitude Migrant College Students by Integrating Artificial Intelligence and Martial Arts Morning Practice
Published in Applied Artificial Intelligence, 2023
As can be seen from the figure, in the clustering results of physical fitness types of male and female students, when K takes a value around 8, the curve starts to level off gradually, so it can be divided into 8 classes more appropriately. z-Score standard score reflects how many standard deviations the obtained data have from the mean, and the farther the z-score standard score is from the value of 0, the larger the data are from the mean, indicating that the quality is more excellent or worse.
Using methods of time series data mining to recognize the influences of environmental factors on bullous pemphigoid
Published in Journal of the Chinese Institute of Engineers, 2018
Jian-Liang Lai, Yu-Ming Chang, Pin-Liang Chen, Lih-Ching Chou, Ding-Dar Lee, Meng-Han Yang
The standard score (z-score) measures the location of a data item in the population distribution. Using z-score, it was important to determine values of BP incidence from certain months that were significantly different from others. The population of z-score calculation consisted of the 12 summed quantities as described above for each month across different years.