Update datacards and scripts for tutorial

data/tutorials/statistical_routines_tutorial/datacard_lowbackground.txt

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+imax 1                         # number of channels
+jmax 1                         # number of backgrounds
+kmax 3                         # number of nuisance parameters
+-------
+shapes * * FAKE
+------
+bin          bin1
+observation     0
+-----
+bin            bin1    bin1
+process         ggH      WW
+process           0       1
+rate            2.3       1
+-------
+lumi     lnN   1.01    1.01    # luminosity uncertainty
+xs_ggH   lnN   1.10       -    # gg->H cross section + signal efficiency + other minor ones
+xs_WW    lnN      -    1.16    # WW cross section + signal efficiency + other minor ones

data/tutorials/statistical_routines_tutorial/datacard_obs12.txt

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+imax 1                         # number of channels
+jmax 1                         # number of backgrounds
+kmax 3                         # number of nuisance parameters
+-------
+shapes * * FAKE
+------
+bin          bin1
+observation     12
+-----
+bin            bin1    bin1
+process         ggH      WW
+process           0       1
+rate            2.3     5.4
+-------
+lumi     lnN   1.01    1.01    # luminosity uncertainty
+xs_ggH   lnN   1.10       -    # gg->H cross section + signal efficiency + other minor ones
+xs_WW    lnN      -    1.16    # WW cross section + signal efficiency + other minor ones

data/tutorials/statistical_routines_tutorial/datacard_underfluctuation.txt

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+imax 1                         # number of channels
+jmax 1                         # number of backgrounds
+kmax 3                         # number of nuisance parameters
+-------
+shapes * * FAKE
+------
+bin          bin1
+observation     13
+-----
+bin            bin1    bin1
+process         ggH      WW
+process           0       1
+rate            2.3     23.4
+-------
+lumi     lnN   1.01    1.01    # luminosity uncertainty
+xs_ggH   lnN   1.10       -    # gg->H cross section + signal efficiency + other minor ones
+xs_WW    lnN      -    1.16    # WW cross section + signal efficiency + other minor ones

data/tutorials/statistical_routines_tutorial/get_quantile.py

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+from ROOT import TFile
+import numpy as np
+import scipy.stats as st
+
+from argparse import ArgumentParser
+
+parser = ArgumentParser()
+parser.add_argument('--input', default="higgsCombineTest.MultiDimFit.mH120.123456.root", help='input root file with toy results from MultiDimFit')
+parser.add_argument('--q0', action='store_true',  help='use the q_0 test statistic rather than the profile likelihood ratio.')
+args = parser.parse_args()
+
+n_sigma = 1
+quantile_val = 2*st.norm().cdf(-n_sigma) #Get the quantile corresponding to the N sigma interval
+
+
+
+f = TFile(args.input,"READ")
+limit = f.Get("limit")
+n_entries = limit.GetEntries()
+
+m2nll_vals = []
+r_vals = []
+last_toy_num = -1
+for i in range(n_entries):
+    limit.GetEntry(i)
+    if limit.quantileExpected < 0:
+        if args.q0:
+            r_vals.append(limit.r)
+        continue
+
+    m2nll_vals.append(2*limit.deltaNLL)
+
+
+test_stat_vals = m2nll_vals
+if args.q0:
+    test_stat_vals = np.where( np.array(r_vals) > 0, test_stat_vals, 0 )
+
+test_stat_cutoff = np.quantile( test_stat_vals, 1-quantile_val)
+t_stat_name = 'q0' if args.q0 else '-2*deltaNLL'
+print(f'This point is rejected at the {n_sigma} sigma level if the test stat {t_stat_name}  > {test_stat_cutoff}')
+