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by: Kiara Lynch

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# Biostatistics exam 2 study guide BIO 472

Marketplace > La Salle University > Biology > BIO 472 > Biostatistics exam 2 study guide
Kiara Lynch
La Salle

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COURSE
Biostatistics
PROF.
TYPE
Study Guide
PAGES
2
WORDS
KARMA
50 ?

## Popular in Biology

This 2 page Study Guide was uploaded by Kiara Lynch on Thursday March 10, 2016. The Study Guide belongs to BIO 472 at La Salle University taught by in Summer 2015. Since its upload, it has received 48 views. For similar materials see Biostatistics in Biology at La Salle University.

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Date Created: 03/10/16
Exam 2 study guide Make a boxplot comparing Alar Extent to Sex boxplot(AlarExtent_mm~Sex, col="lightseagreen", ylab="Alar Extent (mm)", #changes y axis label cex.axis=1.3, #changes size of labels main="Male vs Female Alar Extent", #changes title names=c("Females","Males")) #changes names of groups Make a histogram for Keel_in hist(Keel_in, main="Bumpus Birds Keel Length", #changes title ylab="Length (inches)") #changes y label Make a sacatterplot comparing Keel_in to TotalLength_mm plot(Keel_in~TotalLength_mm, main="Keel Length vs Total Length (mm)", ylab="Keel Length (mm)", xlab="Total Length of Bird (mm)", pch=23, bg="slateblue4", cex=1.5) mean(Keel_in) #finds mean median(Keel_in) #finds median sd(Keel_in) #finds standard deviation tapply(Keel_in, T, mean) #mean for surviving individuals mean(Keel_in) #mean for individuals that did not survive tapply(Keel_in, T, median)#median for surviving individuals median(Keel_in) #median for individuals that did not survive tapply(Keel_in, T, sd) #standard deviation for surviving individuals sd(Keel_in) #standard deviation for individuals that did not survive shapiro.test(Y) Tests that the data is normally distributed; if the p value is > .05 it is normally distributed If the p value is < .05, then you cannot conduct a one sample t test leveneTest(Y~X) Tests that the variances are equal. Reject the null hypothesis that the variances are equal if W>F If p value is <.05 then do welch’s t test If p value is >.05 then do a 2 sample t test t.test(Y~X, alternative=”two.sided”) Conducts a t test where the alternative hypothesis is that the means are not equal. Reject the null hypothesis if 0 is not in the confidence interval The means are significantly different Normally distributed sample shapiro test normality test p value > .05 p value < .05 for both on one or samples both samples Levene p value Levene p value <.05 then > .05 then two Welch's t test sample t test unequal homogeneity of variances variance not significant p value <.05

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