scholarly journals A Simple Method for Generation of Statistical Tables by the Help of Excel Software

2011 ◽  
Vol 2 (1) ◽  
pp. 38-50
Author(s):  
Muhammad Irfan
Keyword(s):  
Normal Distribution ◽  
Poisson Distribution ◽  
Binomial Distribution ◽  
Standard Normal Distribution ◽  
Inverse Transformation ◽  
Chi Square ◽  
Easy Method ◽  
Simple Method ◽  
Standard Normal ◽  
F Distribution

A simple and easy method is employed to construct complete statistical tables like Student’s tdistribution, F distribution, Chi-square distribution and Cumulative standard normal distribution in Excel software which are used in all fields of research. Also, we generate other statistical tables like Cumulative binomial distribution, Cumulative Poisson distribution, Fisher transformation and Fisher inverse transformation. The proposed method depends only on the Excel software; it does not depend on the traditional statistical tables.

Sebaran Peluang Acak Kontinu, Distribusi Normal, Distribusi Normal Baku, Distribusi T, Distribusi Chi Square, dan Distribusi F

2020 ◽  
Author(s):  
Ahmad Sudi Pratikno
Keyword(s):  
Hypothesis Test ◽  
Standard Normal Distribution ◽  
Process Data ◽  
Nominal Data ◽  
Chi Square ◽  
Stable Curve ◽  
Standard Normal ◽  
Research Findings ◽  
F Distribution ◽  
T Distribution

In statistics, there are various terms that may feel unfamiliar to researcher who is not accustomed to discussing it. However, despite all of many functions and benefits that we can get as researchers to process data, it will later be interpreted into a conclusion. And then researcher can digest and understand the research findings. The distribution of continuous random opportunities illustrates obtaining opportunities with some detection of time, weather, and other data obtained from the field. The standard normal distribution represents a stable curve with zero mean and standard deviation 1, while the t distribution is used as a statistical test in the hypothesis test. Chi square deals with the comparative test on two variables with a nominal data scale, while the f distribution is often used in the ANOVA test and regression analysis.

scholarly journals A New Linear Regression Kalman Filter with Symmetric Samples

Symmetry ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 2139
Author(s):  
Xiuqiong Chen ◽  
Jiayi Kang ◽  
Mina Teicher ◽  
Stephen S.-T. Yau
Keyword(s):  
Kalman Filter ◽  
Linear Regression ◽  
Particle Filter ◽  
Normal Distribution ◽  
Extended Kalman Filter ◽  
Nonlinear Filtering ◽  
Unscented Kalman Filter ◽  
Standard Normal Distribution ◽  
Leibler Divergence ◽  
Standard Normal

Nonlinear filtering is of great significance in industries. In this work, we develop a new linear regression Kalman filter for discrete nonlinear filtering problems. Under the framework of linear regression Kalman filter, the key step is minimizing the Kullback–Leibler divergence between standard normal distribution and its Dirac mixture approximation formed by symmetric samples so that we can obtain a set of samples which can capture the information of reference density. The samples representing the conditional densities evolve in a deterministic way, and therefore we need less samples compared with particle filter, as there is less variance in our method. The numerical results show that the new algorithm is more efficient compared with the widely used extended Kalman filter, unscented Kalman filter and particle filter.

The computation of standard normal distribution integral in any required precision based on reliability method

2018 ◽  
Vol 48 (6) ◽  
pp. 1517-1528
Author(s):  
Yuge Dong ◽  
Haimeng Zhang ◽  
Liangguo He ◽  
Can Wang ◽  
Minghui Wang
Keyword(s):  
Normal Distribution ◽  
Standard Normal Distribution ◽  
Reliability Method ◽  
Standard Normal
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