Browsing Statistics by Title
Now showing items 18-37 of 123
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Comparative Classification of Prostate Cancer Data using the Support Vector Machine, Random Forest, Dualks and k-Nearest Neighbours
(North Dakota State University, 2015)This paper compares four classifications tools, Support Vector Machine (SVM), Random Forest (RF), DualKS and the k-Nearest Neighbors (kNN) that are based on different statistical learning theories. The dataset used is a ... -
A Comparative Multiple Simulation Study for Parametric and Nonparametric Methods in the Identification of Differentially Expressed Genes
(North Dakota State University, 2021)RNA-seq data simulated from a negative binomial distribution, sampled without replacement, or modified from read counts were analyzed to compare differential gene expression analysis methods in terms of false discovery ... -
Comparing Accuracies of Spatial Interpolation Methods on 1-Minute Ground Magnetometer Readings
(North Dakota State University, 2017)Geomagnetic disturbances caused by external solar events can create geomagnetically induced currents (GIC) throughout conducting networks of Earth’s surface. GIC can cause disruption that scales from minor to catastrophic. ... -
Comparing Dunnett's Test with the False Discovery Rate Method: A Simulation Study
(North Dakota State University, 2013)Recently, the idea of multiple comparisons has been criticized because of its lack of power in datasets with a large number of treatments. Many family-wise error corrections are far too restrictive when large quantities ... -
Comparing Performance of ANOVA to Poisson and Negative Binomial Regression When Applied to Count Data
(North Dakota State University, 2020)Analysis of Variance (ANOVA) is the easiest and most widely used model nowadays in statistics. ANOVA however requires a set of assumptions for the model to be a valid choice and for the inferences to be accurate. Among ... -
Comparing Prediction Accuracies of Cancer Survival Using Machine Learning Techniques and Statistical Methods in Combination with Data Reduction Methods
(North Dakota State University, 2022)This comparative study of five-year survival prediction for breast, lung, colon, and leukemia cancers using a large SEER dataset along with 10-fold cross-validation provided us with an insight into the relative prediction ... -
Comparing Prediction Methods of Wheat Grain Quality With the Area Under the Receiver Operating Characteristic Curves
(North Dakota State University, 2021)A widely used breeding method is genomic selection, which uses genome-wide marker coverage to predict genotypic values for quantitative traits. Genomic selection combines molecular and phenotypic data in a training population ... -
Comparing Several Modeling Methods on NCAA March Madness.
(North Dakota State University, 2015)This year (2015), according to the AGA’s (American Gaming Association) research, nearly about 40 million people filled out about 70 million March Madness brackets (Moyer, 2015). Their objective is to correctly predict the ... -
Comparing Tests for a Mixed Design with Block Effect
(North Dakota State University, 2009)Tests Comb and Comb II are used to test the equality of means in a mixed design which is a combination of randomized complete block design and completely randomized design. The powers of Comb and Comb II for a mixed ... -
Comparing Total Hip Replacement Drug Treatments for Cost and Length of Stay
(North Dakota State University, 2015)The objective of this study is to identify the potential effect anticoagulants, spinal blocks, and antifibrinolytics have on overall cost, length of stay, and re-admission rates for total hip replacement patients. We use ... -
Comparison of Classification Rates among Logistic Regression, Neural Network and Support Vector Machines in the Presence of Missing Data
(North Dakota State University, 2014)Statistical models such as Logistic Regression (LR), Neural Network (NN) and Support Vector Machines (SVM) often use datasets with missing values while making inferences regarding the population. When inferences are made ... -
A Comparison of False Discovery Rate Method and Dunnett's Test for a Large Number of Treatments
(North Dakota State University, 2015)It has become quite common nowadays to perform multiple tests simultaneously in order to detect differences of a certain trait among groups. This often leads to an inflated probability of at least one Type I Error, a ... -
A Comparison of Filtering and Normalization Methods in the Statistical Analysis of Gene Expression Experiments
(North Dakota State University, 2020)Both microarray and RNA-seq technologies are powerful tools which are commonly used in differential expression (DE) analysis. Gene expression levels are compared across treatment groups to determine which genes are ... -
A Comparison of Methods Taking into Account Asymmetry when Evaluating Differential Expression in Gene Expression Experiments
(North Dakota State University, 2018)Gene expression technologies allow expression levels to be compared across treatments for thousands of genes simultaneously. Asymmetry in the empirical distribution of the test statistics from the analysis of a gene ... -
Comparison of Proposed K Sample Tests with Dietz's Test For Nondecreasing Ordered Alternatives for Bivariate Exponential Data
(North Dakota State University, 2011)Comparison of powers is essential to determine the best test that can be used for data under certain specific conditions. Likewise, several nonparametric methods have been developed for testing the ordered alternatives. ... -
Comparison of Proposed K Sample Tests with Dietz's Test for Nondecreasing Ordered Alternatives for Bivariate Normal Data
(North Dakota State University, 2011)There are many situations in which researchers want to consider a set of response variables simultaneously rather than just one response variable. For instance, a possible example is when a researcher wishes to determine ... -
A Comparison of the Ansari-Bradley Test and the Moses Test for the Variances
(North Dakota State University, 2011)This paper is aimed to compare the powers and significance levels of two well known nonparametric tests: the Ansari-Bradley test and the Moses test in both situations where the equal-median assumption is satisfied and ... -
A Comparison of Two Scaling Techniques to Reduce Uncertainty in Predictive Models
(North Dakota State University, 2020)This research examines the use of two scaling techniques to accurately transfer information from small-scale data to large-scale predictions in a handful of nonlinear functions. The two techniques are (1) using random draws ... -
A Conditional Random Field (CRF) Based Machine Learning Framework for Product Review Mining
(North Dakota State University, 2019)The task of opinion mining from product reviews has been achieved by employing rule-based approaches or generative learning models such as hidden Markov models (HMMs). This paper introduced a discriminative model using ... -
Conditional Random Field with Lasso and its Application to the Classification of Barley Genes Based on Expression Level Affected by Fungal Infection
(North Dakota State University, 2019)The classification problem of gene expression level, more specifically, gene expression analysis, is a major research area in statistics. There are several classical methods to solve the classification problem. To apply ...