scholarly journals Fault Diagnosis Using Clustering. What Statistical Test to use for Hypothesis Testing?

2019 ◽  
Vol 6 (1) ◽  
pp. 17-33 ◽  
Author(s):  
Nagdev Amruthnath ◽  
Tarun Gupta
Keyword(s):  
Fault Diagnosis ◽  
Hypothesis Testing ◽  
Statistical Test

scholarly journals Millenials Lifestyle Phenomenon dan Store Atmosphere terhadap Buying Decision

2019 ◽  
Vol 1 (2) ◽  
pp. 344-355
Author(s):  
Sulastri Fazriah ◽  
Nor Norisanti ◽  
Kokom Komariah
Keyword(s):  
Hypothesis Testing ◽  
Life Style ◽  
Random Sampling ◽  
Research Method ◽  
Linear Analysis ◽  
Statistical Test ◽  
Purchasing Decisions ◽  
F Test ◽  
Analysis Techniques ◽  
Analysis Technique

 The purpose of this study was to determine the effect of store lifestyle on purchasing decisions. The research method in this study uses the type of sample included in the random sampling sample and by distributing questionnaires as many as 100 to consumers. The analysis technique used is multiple linear analysis techniques, and for hypothesis testing is a statistical test using simultaneous (f test). Based on the results of the F test the probability value sig 0,000 <0.1. In conclusion, life style (X1) and Store Atmosphere (X2) have a significant effect on purchasing decisions (Y). Keywords: Purchasing Decisions, Lifestyle, Store Atmosphere

scholarly journals PENGARUH PEMBELAJARAN BERINTEGRASIKAN SCIENCE, TECHNOLOGY, ENGINEERING, AND MATHEMATICS (STEM) TERHADAP HASIL BELAJAR GEOGRAFI DI SMA NEGERI 1 GORONTALO

2021 ◽  
Vol 2 (2) ◽  
pp. 70-77
Author(s):  
Novia Ayu Lestari ◽  
Sunarty Suly Eraku ◽  
Rusiyah Rusiyah
Keyword(s):  
Hypothesis Testing ◽  
Learning Outcomes ◽  
Hypothesis Test ◽  
Learning Model ◽  
Statistical Test ◽  
Learning Cycle ◽  
Average Score ◽  
Control Group ◽  
Normality Test ◽  
And Mathematics

The influence of scoence, technology, engineering, and mathematics (STEM) Integrend Learnng Process on the Learning Outcomes of 1 th Grade Student (An Experimental Research Implementend in SMA 1 State Senior  High School if Gorontalo). This study aimed to determine the differences in learning outcomes of student with the implementation of the Ppa-STEM learning model whilw the control class implemented the learning cycle (5E) learning model on the topic of “population planning and Development Dynamis in Indonesia”. To achieve these objecives, this research employed experimental design with post-test Control Group Design. Data collection techniques involved learning result test, which was provided towards the sample of research. The sample of the study consisted of two classes; class XIb3 of social science as the control class employed the learning cycle (5E) model. During the hypothesis testing, the homogeneity and normality test of the data was conducted in order to conduct hypothesis testing by using parametric statistics. The data normality test employed a chi-square statistical test of the pair of null hypothesis Ho and its match Hi with α = 0,05 significal rate. The test result showed that χ2count χ2table for the experimental class with 3,449 11,070 and the control class of 1,023 9,488. The result revealed that the two data classes can be normally distributed. Based on the results of normality test data, the average score pg students learning outcomes used the statistical test. The hypothesis test results obtained tcount ttable which was 6,58 2,02. All in all, the results revealed that there were differences in the learning outcomes of students who used the two aforeentioned learning models.

Transfer of Training in a Fault Diagnosis Task

1993 ◽  
Vol 37 (18) ◽  
pp. 1272-1276
Author(s):  
Charles T. Dammon ◽  
David M. Lane
Keyword(s):  
Fault Diagnosis ◽  
Hypothesis Testing ◽  
Transfer Of Training ◽  
Task Sharing ◽  
Testing Strategy ◽  
Training Task ◽  
Simple Task ◽  
Far Transfer ◽  
Surface Features ◽  
Complicated Task

Two experiments on the learning and transfer of the hypothesis testing strategy of testing easy-to-test hypotheses first were conducted. The first experiment found that this strategy could be discovered and used in a very simple fault diagnosis task but not in a slightly more complicated task. Subjects who learned the strategy in the simple task were able to transfer it to the more complicated task. The second experiment showed far transfer: The learning of this principle of hypothesis testing transferred to a task sharing no surface features with the training task. It is concluded that it is worthwhile to train people on the use of fault diagnosis strategies.

PENGARUH PERTUMBUHAN EKONOMI, PENDAPATAN ASLI DAERAH, DANA ALOKASI UMUM DAN DANA ALOKASI KHUSUS TERHADAP APBD KOTA PADANG

2010 ◽  
Author(s):  
Arie Frinola Minovia Frinola Minovia
Keyword(s):  
Economic Growth ◽  
Quantitative Analysis ◽  
Hypothesis Testing ◽  
Sampling Method ◽  
Statistical Test ◽  
Analysis Method ◽  
Independent Variables ◽  
Quantitative Analysis Method ◽  
The City ◽  
Two Independent Variables

General, the purpose of this study was to obtain concrete evidence of the influence of economic growth, revenue, special allocation of funds and general funds of the effectiveness of budget allocations the city of Padang. In general, the researchers expect the results obtained in this study may provide benefits to governments, practitioners and researchers themselves. The sample used in this study are several employees who are in a local government environment Padang selected using purposive sampling method. To facilitate the test, the researchers conducted a study that used a variable can be divided into two independent variables of economic growth, local revenues, the general allocation fund and special allocation funds, while the dependent variable is the effectiveness of the budget. To perform the hypothesis testing is used in quantitative analysis method is through the F-statistical test and t test Based on the results of hypothesis testing found that economic growth and the special allocation fund budget efektfitas significant effect on the city of Padang, while local revenues and the general allocation of funds does not significantly influence the effectiveness of Padang city budget. 

scholarly journals The nuts and bolts of hypothesis testing

2015 ◽  
Vol 3 (3) ◽  
pp. 139-144 ◽  
Author(s):  
Stephanie L. Pugh ◽  
Annette Molinaro
Keyword(s):  
Hypothesis Testing ◽  
Hypothesis Test ◽  
Statistical Tests ◽  
Epidemiological Studies ◽  
Statistical Test ◽  
P Value ◽  
P Values ◽  
Multiple Tests ◽  
Alternative Hypotheses ◽  
Decision Making Tool

Abstract When reading an article published in a medical journal, statistical tests are mentioned and the results are often supported by a P value. What are these tests? What is a P value and what is its meaning? P values are used to interpret the result of a statistical test. Both are intrinsic parts of hypothesis testing, which is a decision-making tool based on probability. Most medical and epidemiological studies are designed using a hypothesis test so understanding the key principles of a hypothesis test are crucial to interpreting results of a study. From null and alternative hypotheses to the issue of multiple tests, this paper introduces concepts related to hypothesis testing that are crucial to its implementation and interpretation.

Statistical Test of Difference between Expected Accident Frequencies

1996 ◽  
Vol 1542 (1) ◽  
pp. 24-29 ◽  
Author(s):  
Ezra Hauer
Keyword(s):  
Hypothesis Testing ◽  
Road Safety ◽  
Companion Paper ◽  
Statistical Test ◽  
Statistical Hypothesis ◽  
Statistical Hypothesis Testing ◽  
Accident Frequency ◽  
Specific Circumstance ◽  
Statistical Hypotheses ◽  
The Right

A primer on the testing of some common statistical hypotheses in road safety is presented. The basic notions of statistical hypothesis testing are reviewed and applied to the specific circumstance when one wishes to test a statistical hypothesis about a change in the expected accident frequency beyond what is the result of a change in traffic and similar influences. The hope is that this exposition will illumine the meaning and intricacy of such tests, inform the decision about when such tests are called for, help users choose the right significance or power, and, because software is now available, improve practice in this matter. A companion paper on the detection of deterioration in safety makes use of the foundation provided.

Hypothesis Testing in Non-Linear Models Exemplified by the Planar Coordinate Transformations

2018 ◽  
Vol 8 (1) ◽  
pp. 98-114 ◽  
Author(s):  
R. Lehmann ◽  
M. Lösler
Keyword(s):  
Hypothesis Testing ◽  
Likelihood Ratio ◽  
Likelihood Ratio Test ◽  
Statistical Test ◽  
Monte Carlo Integration ◽  
Ratio Test ◽  
Coordinate Transformations ◽  
Test Power ◽  
Non Linear ◽  
Decision Errors

Abstract In geodesy, hypothesis testing is applied to a wide area of applications e.g. outlier detection, deformation analysis or, more generally, model optimisation. Due to the possible far-reaching consequences of a decision, high statistical test power of such a hypothesis test is needed. The Neyman-Pearson lemma states that under strict assumptions the often-applied likelihood ratio test has highest statistical test power and may thus fulfill the requirement. The application, however, is made more difficult as most of the decision problems are non-linear and, thus, the probability density function of the parameters does not belong to the well-known set of statistical test distributions. Moreover, the statistical test power may change, if linear approximations of the likelihood ratio test are applied. The influence of the non-linearity on hypothesis testing is investigated and exemplified by the planar coordinate transformations. Whereas several mathematical equivalent expressions are conceivable to evaluate the rotation parameter of the transformation, the decisions and, thus, the probabilities of type 1 and 2 decision errors of the related hypothesis testing are unequal to each other. Based on Monte Carlo integration, the effective decision errors are estimated and used as a basis of valuation for linear and non-linear equivalents.

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