import numpy as np
import fetchmaker
rottweiler_tl = fetchmaker.get_tail_length('rottweiler')
print(np.mean(rottweiler_tl), np.std(rottweiler_tl))
whippet_rescue = fetchmaker.get_is_rescue('whippet')
num_whippet_rescue = np.count_nonzero(whippet_rescue)
print(num_whippet_rescue)
num_whippets = np.size(whippet_rescue)
print(num_whippets)
from scipy.stats import binom_test
whippet_binom_test = binom_test(num_whippet_rescue, num_whippets, 0.08)
if whippet_binom_test < 0.05:
print('Significant Difference!')
else:
print('No Difference.')
from scipy.stats import f_oneway
whippet_avg_weight = fetchmaker.get_weight('whippet')
terrier_avg_weight = fetchmaker.get_weight('terrier')
pitbull_avg_weight = fetchmaker.get_weight('pitbull')
weight_t, weight_pval = f_oneway(whippet_avg_weight, terrier_avg_weight,
pitbull_avg_weight)
if weight_pval < 0.05:
print('There is a difference between these breeds!')
else:
import numpy as np
import fetchmaker
from scipy.stats import binom_test
from scipy.stats import f_oneway
from statsmodels.stats.multicomp import pairwise_tukeyhsd
from scipy.stats import chi2_contingency
rottweiler_tl = fetchmaker.get_tail_length("rottweiler")
print(np.mean(rottweiler_tl))
print(np.std(rottweiler_tl))
"""
Over the years, we have seen that we expect 8% of dogs in the FetchMaker system to be rescues. We want to know if whippets are significantly more or less likely to be a rescue.
"""
whippet_rescue = fetchmaker.get_is_rescue("whippet")
num_whippet_rescues = np.count_nonzero(whippet_rescue)
print(num_whippet_rescues)
num_whippets = np.size(whippet_rescue)
print(num_whippets)
pval = binom_test(num_whippet_rescues, n=num_whippets, p=0.08)
print(pval)
"""
Three of our most popular mid-sized dog breeds are whippets, terriers, and pitbulls. Is there a significant difference in the average weights of these three dog breeds? Perform a comparative numerical test to determine if there is a significant difference.
"""
whippet_weight = fetchmaker.get_weight("whippet")
terrier_weight = fetchmaker.get_weight("terrier")
pitbull_weight = fetchmaker.get_weight("pitbull")
print(np.size(whippet_weight))
print(np.size(terrier_weight))
print(np.size(pitbull_weight))
import fetchmaker as fm
import numpy as np
from scipy.stats import binom_test
from scipy.stats import f_oneway
from statsmodels.stats.multicomp import pairwise_tukeyhsd
from scipy.stats import chi2_contingency
rottweiler_tl = fm.get_tail_length("rottweiler")
print(np.mean(rottweiler_tl))
print(np.std(rottweiler_tl))
whippet_rescue = fm.get_is_rescue("whippet")
num_whippet_rescues = np.count_nonzero(whippet_rescue)
num_whippets = np.size(whippet_rescue)
pval = binom_test(num_whippet_rescues, num_whippets, p=0.08)
print(pval)
# pval > 0.05 : Not significant
whippet_wg = fm.get_weight("whippet")
terrier_wg = fm.get_weight("terrier")
pitbull_wg = fm.get_weight("pitbull")
pval2 = f_oneway(whippet_wg, terrier_wg, pitbull_wg).pvalue
print(pval2)
# pval > 0.05 : Not significant
weights = np.concatenate([whippet_wg, terrier_wg, pitbull_wg])
labels = ["Whippet"] * len(whippet_wg) + ["Terrier"] * len(terrier_wg) + ["Pitbull"] * len(pitbull_wg)
