STAT 3006 Lecture Notes - Fall 2018 Lecture 4 - Type I and type II errors, Dependent and independent variables, Null hypothesis
21 Sep 2018
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If we wanted to compare the means of some quantitative variable for two populations, we would use two-sample t-procedures. If we want to test more than two groups, we can use an analysis of variance (anova) test. (cid:4666) (cid:2778) (cid:2779)(cid:4667) (cid:2777) Variance: a representation of the spread of data. Apply the variance concept to means, which reflects the uncertainty regarding the values of the unknown means. Variance within groups: variability or differences in particular groups (individual differences). Between groups: differences depending what group one is in or what treatment is received. Analysis of variance tests whether several populations have the same means by comparing how far apart the sample means are with how much variation there is within a sample. The purpose of anova is to assess whether the observed differences among sample means are statistically significant. Anova can be one way, two way, etc. based on the amount of quantitative variables you have.
