I'm new to CV, so please excuse any faux pas. I've collected sample data from a population and would like to discern whether or not the experimental group outperforms the control group. Let's say I have 10,000 observations within the experimental group and saw 4500 successes. Let's also say that I observed a 47% success rate in my control group (so if my control group is 5% of the total sample size, that would be 235 successes out of 500 trials).
Now, am I right in my usage and interpretation of the following?:
prop.test(4500,10000,.47,alt="less") data: 4500 out of 10000, null probability 0.47 X-squared = 15.9776, df = 1, p-value = 3.205e-05 alternative hypothesis: true p is less than 0.47 95 percent confidence interval: 0.0000000 0.4582455 sample estimates: p 0.45
Since the p-value is far less than .05, I can safely reject the null hypothesis that that the experimental group will perform as well or better than the control group. Also, I know that 95% of the time, the probability of success for the experimental group will fall between 0% and ~45.8%.
Also, is the
prop.test function a good indicator of sufficient sample size? If not, what is?