Python code to give the confidence interval for two sample test. Uses z and t-distributions, without the need of look-up tables. Data can be extracted from any column in an ascii or csv file.
Can be run directly here
E.g. Data with the two samples to compare? 3.15_apples.dat
For NY - n = 10, mean = 3.941, SD = 0.184 [sample]
For LA - n = 8, mean = 3.245, SD = 0.268 [sample]
Level of confidence [e.g. 95, 99, 99.9% - z = 3 sigma is 99.75]? 95
At least one sample size < 30 so using t-value
Variance ratio is 0.47,
Assume equal sample variances (for ratio between 0.5 and 2 can assume equal) [y/n]? y
For 95.00% confidence (16 DoFs), t-value is 2.120, giving mean diff of 0.70 +/- 0.23 (0.47 to 0.92)
For 99.90% confidence (16 DoFs), t-value is 4.006, giving mean diff of 0.70 +/- 0.43 (0.27 to 1.12)
For one sample version see https://github.com/steviecurran/one-sample