Help! Which test do I use and how?! *very rusty graduate*

[statsman1]

Hi all

I have been given some data and I need to do some significance testing on it.

The data revolves around food types. Firstly I have been given data, about 1000 rows, of a food type with the date the food was bought and date it went off, I need to test whether after X number of days, a significant number of the food has expired.

So simply put, I have data on about 1000 types of a food, with the number of days it stayed edible and I need to check whether a day X=a the food becomes significantly bad.

I also have further data on the food; location grown, conditions grown, food used etc. So after this I would like to calculate similar tests to see whether these conditions are also significant.

I hope this all makes sense and I welcome any help you guys can give!

Thanks!

 

[jpkelley]

We might need a bit more detail. You have 1000 different food types? Do you replicates of these "types" (food type= fruit, fruit = banana or apple or orange)? From your description, it sound like the only thing you can do is estimate the distribution of "times until expiration" but perhaps you can provide a fake dataset to demonstrate your data structure?

 

[statsman1]

No I have data on 1000 of the same food, say I have info on 1000 oranges about when they went out of date. I have found the rates and which they expire which is kind of helpful.

I was thinking I could do an hypothesis test. After say 90 days, to see statistically whether there's evidence that H0: p <= p0, H1: p > p0. p=0.21 since about 21% of the food expires before 90 days, then this could be tested to against p=0.2 say? From this Z_calc = -2.42 since n=990.

I would like to look at rate of decay and get confidence intervals on the average rate of food decay on a per day basis, but not to sure how to approach it...?