Exam II Marks. Chapter 20.1 Correlation Correlation is used when we wish to know whether two randomly distributed variables are associated with each.

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Presentation transcript:

Exam II Marks

Chapter 20.1 Correlation

Correlation is used when we wish to know whether two randomly distributed variables are associated with each other Example – Total length Y1 of aphid stem mothers and mean thorax length Y2 of their parthenogenetic offspring.

No causal ordering

Contrast to regression

Formal model Regression randomly distributed response variable ~ fixed explanatory variable Correlation two random response variables No causal ordering, thus no explanatory variable

Compute t

State H A /H o pair Crunch the numbers

More number crunching > cor.test(dat$th.length,dat$tot.length) Pearson's product-moment correlation data: dat$th.length and dat$tot.length t = , df = 13, p-value = alternative hypothesis: true correlation is not equal to 0 95 percent confidence interval: sample estimates: cor

Conclusions r = 0.650, n = 15, p = Thorax length of offspring is positively related to stem mother total length. The relation of offspring thorax length to size of aphid stem mothers is monotonic but not necessarily linear.