location_id	aqi_2000	aqi_2020
USC00203823	11	16
USC00276818	1	1
USC00186620	4	1
USC00331890	18	15
USC00235987	59	51
USC00395691	39	18
USC00219046	23	17
USW00003812	17	3
USC00047643	46	65
USW00013896	67	104
USC00315838	49	39
SWE00137512	0	0
ASN00072150	34	62
USC00478827	35	3
USW00013963	71	86
USC00049325	100	117
GME00130870	2	10
USC00410902	101	104
USC00326315	28	19
USW00014847	5	7
USC00509641	2	1
USW00013734	20	26
USC00216787	9	4
USC00331458	6	13
USC00419800	123	117
USC00134894	35	29
USC00451276	5	12
USC00391972	43	42
GME00126394	4	18
NOM00001492	0	2
USC00444876	7	30
GME00122602	0	15
USC00226177	102	80
USC00397742	23	12
GME00121270	0	2
GME00125218	0	14
USC00354003	11	31
USW00012843	28	84
USC00303773	5	4
USC00351407	3	27
USC00087205	121	160
USC00501987	0	1
USC00163313	131	70
USC00471568	19	9
USW00023271	52	90
USW00014860	6	15
USW00014607	0	2
USW00026411	2	0
USC00112483	59	34
USC00203661	23	17
USC00451679	1	6
USW00013996	49	77
USW00014929	35	31
GME00121966	1	4
USC00330862	20	19
USC00420086	0	24
USW00014920	26	24
USC00035908	102	94
USC00471078	35	15
USC00105275	0	3
USC00306774	16	18
USW00013729	3	4
USC00389350	57	61
USC00301752	10	2
USC00165266	110	122
USC00392429	37	58
USC00307134	6	9
USC00391392	47	14
USC00253660	56	31
USC00047643	46	65
USW00014768	15	22
USC00471078	35	15
ASN00023013	28	60
USC00210075	18	10
USC00401145	44	88
USC00053005	23	37
USW00023179	163	186
USW00014944	31	15
GM000010147	1	9
GME00124318	6	16
USC00437054	10	13
USC00338822	13	17
USC00312837	8	2
ASN00031011	25	61
GM000004204	5	17
USC00380165	58	64
USC00200779	11	14
USC00031730	104	129
USC00273850	10	17
USC00381633	62	61
USW00003122	2	7
GME00127462	1	1
USW00013977	95	104
USC00393294	39	25
USC00124662	44	16
USW00014768	15	22
USC00333758	45	18
USC00137147	26	21
GME00122638	3	14
SPE00120620	17	48
USC00331890	18	15
USC00256375	33	35
USW00024227	4	14
USC00108022	10	6
USC00044890	101	122
USC00336465	22	21
USW00013733	23	35
SPE00120458	5	2
USC00354003	11	31
USC00032540	113	82
USC00425148	1	6
USC00242409	10	13
USW00024028	44	51
USW00014739	12	23
EI000003969	0	0
USC00141435	71	78
USW00023272	0	0
USC00245740	10	22
USC00325220	26	19
USC00381633	62	61
USW00025506	0	0
USC00104831	12	24
USC00216565	20	12
USC00475017	5	0
USC00046377	0	0
USC00335857	25	10
USC00237720	39	45
USC00254455	50	26
USC00238444	40	74
USW00013970	87	126
GME00126322	0	0
SPE00120161	20	32
GME00121654	0	10
USC00140682	65	57
USC00410902	101	104
USC00415272	143	129
USC00254455	50	26
USC00046719	26	74
USC00123547	29	7
SZ000001940	1	12
USW00094849	10	15
USC00398472	57	19
NLM00006260	0	3
USW00093837	80	107
USC00449301	7	3
GME00102220	1	2
USC00218692	23	13
USW00024121	47	57
USC00179891	11	7
USC00476678	11	10
USC00012813	82	86
USW00013873	55	92
USC00314970	53	55
USC00387722	70	82
USW00093820	29	33
USC00207812	7	2
USC00242122	32	29
USC00145363	64	80
USC00103297	35	31
USC00399442	57	35
USC00350897	4	16
USC00052184	0	1
USC00261358	80	108
USC00138806	36	17
USW00023155	104	110
USC00351682	2	1
SPE00120458	5	2
USC00404858	32	33
USC00115079	49	26
USW00014935	46	37
USC00317994	60	82
USC00051959	0	0
USC00318500	71	58
USC00395481	45	22
USW00024131	27	55
USW00094728	13	21
GME00130870	2	10
USC00031948	73	85
USC00352997	16	32
USC00392429	37	58
USC00306774	16	18
USC00217405	43	11
USC00351407	3	27
USW00023065	57	59
USW00014804	10	12
USW00014935	46	37
USW00014850	7	16
USW00024225	24	63
USW00014941	38	29
SP000008416	6	10
USC00094648	32	0
GME00128014	1	18
USC00405187	50	77
USC00137386	19	12
USC00411048	133	105
NLM00006235	0	1
USW00026411	2	0

This question focuses on comparing two different years, 2000 and 2020, by examining statistics on air quality. We are using a historical dataset from the Environmental Protection Agency that contains information on air pollution for 197 randomly selected locations that have been measured twice, once in 2000 and in 2020. The terms "aqi_2000" and "aqi_2020" in this dataset denote the number of days in 2000 and 2020, respectively, that the Air Quality Index (AQI) exceeded 100, signifying poor air quality. The goal is to ascertain whether there is substantial evidence pointing to a rise in the number of days in 2020 compared to 2000 with poor air quality (AQI > 100).

a)Are "aqi_2000" and "aqi_2020" data points independent of one another? Do these two variables have any relationship? Describe.

b)Determine the difference between 2000 and 2020 in terms of the number of days with an AQI greater than 100. To show how these differences are distributed, make a graph using excel. Remark on the distribution's normalcy.

c)Calculate the differences' mean and standard deviation using excel. To explore the hypothesis that 2020 had more days with bad air quality (AQI > 100) than 2000, run a parametric test. Make use of the p-value method and a 5% significance level.Don't forget to include the following steps: p-value, choice rule, hypothesis creation, and a well-reasoned conclusion. For verification, provide a excel screenshotin addition to manualcomputations. (Using exceland manual computations)

d)Provide a 95% confidence interval that is one-sided for the mean difference in the number of days where the AQI is more than 100. (manual calculation)

e)Does the result drawn from the hypothesis test seem supported by the confidence interval from section (d)? Give a justification.

d)Determine whether the parameters needed for the confidence interval and parametric hypothesis test were met in this instance. Talk about if a parametric test is appropriate for this dataset.