CODEWITHSUNDEEP
rstatistics
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Reputation: 473

prop.test alternative statement usage

I am testing if a sending information to consumers about promotion convince them to buy anything. Out of 100k consumers we randomly selected 90% of them and sended them catalogs. After sometime we tracked who have bought.

To recreate the problem lets use:

set.seed(1)
got <- rbinom(n=100000, size=1, prob=0.1)
bought <- rbinom(n=100000, size=1, prob=0.05)

table(got, bought)
   bought
got     0     1
  0 85525  4448
  1  9567   460

As I read on here I should use prop.test(table(got, bought), correct=FALSE) function, but i want to check not only if the proportions are equal, but if the proportion of those who bought during promotion, for the group who got the leaflet was greater then in those who didn't get it.

Should I use argument alternative = "less" or , alternative = "greater"? and dose the order or got and bought is impotent?

Upvotes: 2

Views: 249

Answers (1)

Robin Gertenbach
Robin Gertenbach

Reputation: 10806

You usually want to use a two sided alternative (for all you know sending promotion annoys people and they are less likely to purchase).

prop.test is doing a chi square test which by definition does not look at which group is bigger.

You could do a t.test like this

t.test(bought ~ got, data = data.frame(got = got, bought = bought))

Depending on your typical conversion rate and sample size and alpha you can get confidence intervals implying negative conversion rates so a Bootstrapping or Bayesian approach may be better suited.

Upvotes: 2

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