# How to calculate Odds Ratio with R

I have a dataset that looks like this:

> scores
date scores price
1  30/11/2017      1     1
2  01/12/2017      1     0
3  02/12/2017      0     1
4  03/12/2017      1     0
5  04/12/2017      1     1
6  05/12/2017      1     0
7  06/12/2017      1     0
8  07/12/2017      1     1


I would like to calculate the odds ratio but I can't seem to find a way. Is there an easy way to do it?

UPDATE

I've used the questionr package and the odds.ratio function and I've obtained this:

> odds.ratio(table(scores$scores, scores$price))
OR   2.5 % 97.5 %      p
Fisher's test 2.18493 0.58581 8.4658 0.2374


EDIT

Basically I'm doing a project for my university. I have binarized sentiment scores for each day (0 if they are under a mean score and 1 if above) and binarized stock price variations (0 if price is lower than previous day, 1 if above). My teacher suggested to run odds ratio to see if sentiment by investor could influence the price variations, so I did it, but I dont know how to interpret them since all I can find about odds ratio are examples with presence/absence of a desease. My guess was that when the sentiment is positive (value of 1, and I will consider this class as the "exposure" class of the medical examples) the stock price has a possibility to increase (value of 1, considered as the "oucome" class) that is 2.1 times bigger than it would be with a negative sentiment (value of 0). But I'm absolutely NOT sold on this interpretation

• Ok, thanks for the help, I'll read the link. Thanks again – TheClutch01 Mar 17 '18 at 20:49
• One thing that I wanted to point out here is that these data have been collected over time so they likely exhibit temporal dependence. If this dependence is ignored, subsequent inferences may be invalid. – Isabella Ghement Mar 17 '18 at 23:11