# How do I interpret these results for a Proportion Test in R?

> prop.test(table(D2$SMOKE,D2$RACE),correct=FALSE)

2-sample test for equality of proportions without continuity correction

data:  table(D2$SMOKE, D2$RACE)
X-squared = 23.26, df = 1, p-value = 1.415e-06
alternative hypothesis: two.sided

95 percent confidence interval:
0.1863890 0.3809326

sample estimates:
prop 1: 0.7733333
prop 2:  0.4896725

• what is your hypothesis? How do you compute proportions ? IS there any logic to use chi- square statistic for your study ? – Subhash C. Davar Nov 15 '17 at 16:05

prop1 and prop2 are the probabilities of success for your 2 groups. the p-value is less than one minus the level (95% or 0.95) of the confidence interval, which indicates the proportions of the characteristic studied are statistically significantly different in the 2 groups.
• Generally, we also ignore the $\chi^2$ (X-squared) value and the df (degrees of freedom) since the confidence interval contains all the information we need. We can also conclude that the proportion difference is statistically significantly different because the confidence interval does not contain 0 (indicating no proportion difference). – AdamO Nov 14 '17 at 19:00