Προγραμματιστής: | ivan gabrovski (29) | ||
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Περιγραφή
Component processing samples of random variables is designed to store (edited, deleted, renamed) samples of random variables, to calculate their basic statistical characteristics as the: -average value; - standard deviation; - skewness and kurtosis; - to calculate confidence intervals of the average value; - variance and standard deviation; - check whether the sample is from normal or uniformly distributed random variable using criterion of Pearson; - check whether the sample is from normal, uniformly and exponentially distributed random variable using criterion of Kolmogorov-Smirnov; - and zero skewness and kurtosis; - determined histogram of sample; - function testing of hypotheses related to the mean and standard deviation; and other.
The application has function for smooth distributions, this includes assets for visualization adjusted( smooth) distributions related to the sample, not excluded from the Pearson's and Kolmogorov-Smirnovr's criteria.
In the component Factors Analysis for correlation matrix factorization applies two known methods: main components (Pearson, 1901 and Hoteling, 1933); and - the main factors (Spearman, 1904 1926). A correlation matrix can be obtained by treatment of data with functions of the application, or by entering or importing into the application of ready-correlation matrices.
Samples, results of processing and histogram can be saved . Tables with these data can be exported, and sending for saving and printing. The application has functions for create, delete and selection of a folder for storage data results.
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Factor Analysis for Android
The app Factors Analysis for Android consists three components, one is processing samples of random variables; the secondis factorization of correlation matrix; and the third calculator for the known statistical distributions.
app is to store many samples of random variables and to calculate correlation matrix
processing sample of random variables
check whether the sample is from normal or uniformly distributed random variable using criterion of Pearson; and Kolmogorov-Smirnovr's criteria
determined histogram of sample;
applies two methods main components and the main factors for correlation matrix factorization
calculating cumulative probability or random variable
results data can be exported and sending by Internet
create, delete and selection of a folder for storage data results
hypotheses, histogram random probability statistical distributions correlation matrix factorization main components factors
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