Multivariate Analysis Commons^™

Manova: Type I Error Rate Analysis, Kyle Wesley Gasperik

Statistics

Multivariate analysis of variance (MANOVA) is most commonly used in the field of bio-statistics. Throughout this paper I conduct numerous simulations that help analyze how robust the MANOVA procedure is against its assumptions. Using Type I error rate as my measure of error, I used the R software to graph my results. The main assumption that is focused on is the equal covariance matrix assumption, which we introduce correlation between variables to see how well the MANOVA procedure performs. Overall, 70 simulations were ran, and 10 functions were created to perform all of the analysis.

Investigation Of Mlb Data With Multivariate Statistics, Vincent Milano

Statistics

A statistical study was performed in order to explore the relationships of the offensive player statistics for every player in the 2008 Major League Baseball season. The purpose of the study was to explore various multivariate statistical methods within the data set.

The offensive variables in the study are: games, at-bats, runs, hits, singles, doubles, triples, homeruns, extra base hits, runs batted in, total bases, walks, strikeouts, stolen bases, times caught stealing, on-base percentage, slugging percentage, on-base plus slugging percentage, and batting average. All variables are season totals except for onbase percentage, slugging percentage, on-base plus slugging, and batting average. …