query: Comparing Standard Errors, t-Statistics, P-Values, Logistic Curve Fitting Exercise
positive_passages.docid: 148695
positive_passages.text: Comparing Growth Curve P-Values, Different Length Data Sets
negative_passages.docid: 83222
negative_passages.text: using trial and error in math problems
negative_passages.docid: 128694
negative_passages.text: Plotting confidence intervals for the predicted probabilities from a logistic regression
negative_passages.docid: 39991
negative_passages.text: Multiple hypothesis testing with FDR in R - FDRtool and p.adjust
negative_passages.docid: 80568
negative_passages.text: Using wilcox.test() and t.test() in R yielding different p-values
negative_passages.docid: 51840
negative_passages.text: The standard normal distribution vs the t-distribution
negative_passages.docid: 66062
negative_passages.text: Test logistic regression model using residual deviance and degrees of freedom
negative_passages.docid: 107278
negative_passages.text: Comparing SVM and logistic regression
negative_passages.docid: 96379
negative_passages.text: Choosing the appropriate statistical test
negative_passages.docid: 127435
negative_passages.text: Estimating parameters of Student's t-distribution
negative_passages.docid: 49381
negative_passages.text: Simulation of logistic regression power analysis - designed experiments
negative_passages.docid: 107720
negative_passages.text: Resampling / simulation methods: monte carlo, bootstrapping, jackknifing, cross-validation, randomization tests, and permutation tests
negative_passages.docid: 55841
negative_passages.text: Fisher's exact test: 95% CI or p-value
negative_passages.docid: 11124
negative_passages.text: Normality of residuals vs sample data; what about t-tests?
negative_passages.docid: 84328
negative_passages.text: Wald test in regression (OLS and GLMs): t- vs. z-distribution
negative_passages.docid: 97787
negative_passages.text: 5 Likert Scale and Normal Distribution prior to parametric testing
negative_passages.docid: 144448
negative_passages.text: Understanding lack of fit in logistic regression