[FIXED] How to perform TTest on multiple columns

Issue

My dataframe is below

patid age gender    tg0 tg1 tg2 tg3 tg4 wgt0 wgt1 wgt2 wgt3 wgt4
0   1   45  Male    180 148 106 113 100 198 196 193 188 192
1   2   56  Male    139 94  119 75  92  237 233 232 228 225
2   3   50  Male    152 185 86  149 118 233 231 229 228 226
3   4   46  Female  112 145 136 149 82  179 181 177 174 172
4   5   64  Male    156 104 157 79  97  219 217 215 213 214

Is it the right way If I do the average of tg0 tg1 tg2 tg3 tg4 and wgt0 wgt1 wgt2 wgt3 wgt4 so that i will get 2 columns a and b and do the ttest

Copying the case study also

A physician is evaluating a new diet for her patients with a family history of heart disease. To test the effectiveness of this diet, 16 patients are placed on the diet for 6 months. Their weights and triglyceride levels are measured before and after the study, and the physician wants to know if either set of measurements has changed

Null hypothesis: There is no difference in the levels of Triglycerides and weight of individual after using new diet for 6 months.

Alt hypothesis: There is has been a significant difference in the levels of Triglycerides and weight of individual after using new diet for 6 months.

For 2 variable we can do like below code

from scipy import stats
#Data of group 1
a = np.array([42.1, 80.0, 30.0, 45.8, 57.7, 80.0, 82.4, 66.2, 66.9, 79.0])
#Data of group 2
b = np.array([80.7, 85.1, 88.6, 81.7, 69.8, 79.5, 107.2, 69.3, 80.9, 63.0])
t2, p2 = stats.ttest_ind(a,b)

Solution

It looks like you want to find the difference before and after the 6 month period for each measurement type. Based on this, it seems that you would want to do two separate tests:

1. Whether the final triglyceride measurement value significantly differs from the initial triglyceride measurement.
2. Whether the final weight measurement value significantly differs from the initial weight measurement.

Note: I'm assuming that each column represents a measurement over time, starting with 0 and ending with 4. This would mean that tg0 and wgt0 are the initial triglyceride and weight measurements respectively, and that tg4 and wgt4 are the final measurements

For each test, you are comparing the final measurement with the initial measurement, so you would want to structure the tests like this:

t_tg, p_tg = stats.ttest_ind(tg4,tg0)
t_wgt, p_wgt = stats.ttest_ind(wgt4,wgt0)

Then use p_tg and p_wgt to make a unique determination for the triglycerides and the weight.

Answered By - Rylan Polster

Answer Checked By - Candace Johnson (PHPFixing Volunteer)