Statistical Inference

Assumption: Assume that df is a DataFrame, ser is a Series, arr is an array, and we already run import babypandas as bpd and import numpy as np.

This section provides explanations and code implementations of theories covered in DSC 10. For examples in this section, refer to the full_pets DataFrame, which has more data than pets DataFrame (which is used in the Documentation section).

full_pets

Index	ID	Species	Color	Weight	Age	Is_Cat	Owner_Comment
0	dog_001	dog	black	40	5	False	There are no bad dogs, only bad owners.
1	cat_001	cat	golden	1.5	0.2	True	My best birthday present ever!!!
2	cat_002	cat	black	15	9	True	**All you need is love and a cat.**
3	dog_002	dog	white	80	2	False	Love is a wet nose and a wagging tail.
4	dog_003	dog	black	25	0.5	False	Be the person your dog thinks you are.
5	ham_001	hamster	black	1	3	False	No, thank you!
6	ham_002	hamster	golden	0.25	0.2	False	No, thank you!
7	cat_003	cat	black	10	0	True	No, thank you!
8	dog_004	dog	black	45	6.7	False	No, thank you!
9	dog_005	dog	white	10	7	False	No, thank you!
10	dog_006	dog	golden	35	4	False	No, thank you!
11	cat_004	cat	black	10	1.2	True	No, thank you!
12	cat_005	cat	white	15	2.5	True	No, thank you!
13	ham_003	hamster	black	0.5	0.1	False	No, thank you!
14	dog_007	dog	white	50	6.1	False	No, thank you!
15	ham_004	hamster	golden	0.25	0.2	False	No, thank you!
16	dog_008	dog	black	40	5	False	No, thank you!
17	dog_009	dog	white	30	4.8	False	No, thank you!
18	cat_006	cat	black	3	0.5	True	No, thank you!

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