H_0b: positive relationship between female and survival.H_0a: no association between female and survival. ![]() I'm assuming that you want to test two null hypotheses: If the null hypothesis is “Female has a better survival rate”, how shall I change the testing process? so I can’t reject the null hypothesis.Īm I doing the right thing in hypothesis testing? If not, where's the problem? Z.test2(as.numeric(female_data$status), as.numeric(a.data$status), female_data)Īs the Z score is between -1.96 and +1.96, the p-value will be larger than 0.05. Zeta = (sample_mean - pop_mean) / (sd(b) / sqrt(c)) In R: a.data <- read.csv("")įemale_data <- subset(a.data, a.data$sex = "F") I want to calculate the Z score to test the hypothesis. Here are my hypothesis statements: Hº: Gender has no significant difference in survival ![]() In learning of hypothesis testing, I want to see if different gender has the same survival rate.
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