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Defn-Exam 2-Geog 339

# Defn-Exam 2-Geog 339 - Geog 339 Definitions Wilcoxon Rank...

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Geog 339 Definitions - Wilcoxon Rank Sum Test : data are ordinal; compare two independent random sample rank sums for difference. - ANOVA : determine which is more dominant; between group variability or within. F>F cutoff : reject null - Between-group variability : how the sample mean of each group differs from the total mean when all categories are grouped together. - Within-group variability : measures the variation of observations in each group about the mean of that group. - Independent Samples : items collected from one sample do not relate to items collected in the other sample. - Dependent Samples : matched pairs of observations (sampling the same thing before and after event- Matched-pairs). - Parametric : interval and ratio scale, require population parameters to be estimated using samples; make assumptions about the underlying distribution (normal). - Non-Parametric : ordinal scale (ranked), non-normal distribution, no parameter estimates. - PVE : pooled variance estimate - when equality of variances is assumed in a two-sample difference of means t-test, longer formula for denominator. - SVE : separate variance estimate - when variances are not assumed equal - Type I error : the probability of rejecting a true NULL hypothesis - more serious, = α. - Type II Error : the prob ability of accepting a false NULL hypothesis, = β. - One-tailed test : directional - area to right of α is rejected, are to left accept, H O : u=u1, H A : u<u1. - Two-tailed test : non-directional - area= α/2, area between the two α's accept H O , outside area reject H O . - INFERENTIAL STATISTICS : methods used to make inferences about a population from a sample. - Inferential Test : a specific test chosen because it suits the particular problem at hand (e.g., difference of means). - Null Hypothesis : Claim for equality - no significant difference between samples. - Alternate Hypothesis : condition under which null is rejected, and a statement of difference between samples. - Goodness-of-fit : Actual frequency distribution tested against an expected frequency distribution.

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- K-S test for Normality : compares the cumulative relative frequencies (CRF) of observed sample data with that of a perfect normal distribution. If the two OGIVEs “match”, the sample distribution can be considered normal. CRF e = CNV in formula sheet, CRF o = x/n, 1/7, 2/7 cumula - CHI-Square GoF : determine if a truly significant difference exists between observed and expected frequencies - Contingency Analysis : Frequency distributions between two variables are compared with one
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Defn-Exam 2-Geog 339 - Geog 339 Definitions Wilcoxon Rank...

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