Analyze energy data using Minitab

Energy Usage

A medical device manufacturer has been collecting data on a variety of weather-related variables (e.g Avg Monthly Temp) as well as some operational data (e.g Monthly units produced) for one of their manufacturing facilities. Using an appropriate statistical modeling technique, create a model that is able to forecast monthly energy use going forward. Which metrics are most explanatory at describing energy use in a given month? Which ones are the least important but still helpful in forecasting? And which ones do not appear to be useful at all? provide the model equation in your presentation along with a detailed summary interpretation of the output.

Data for the problem

Month Year	Avg Temp	Min Temp	Max Temp	Pct Sun	Units Produced	Total Equip Run Time	Energy
Jan-14	50	39	62	63	1202	2452	37176
Feb-14	55	43	65	64	1326	3181	39892
Mar-14	61	48	71	76	1121	2312	39270
Apr-14	66	56	76	74	1741	3393	42425
May-14	74	62	84	76	1124	2730	39392
Jun-14	78	69	89	78	1306	2819	41800
Jul-14	81	72	90	75	1568	2888	42967
Aug-14	81	71	90	73	1413	2747	44130
Sep-14	74	68	87	68	1684	2726	40948
Oct-14	68	55	83	72	1555	3224	41700
Nov-14	57	46	70	63	1661	3110	39508
Dec-14	53	44	62	65	1215	2604	35315
Jan-15	49	38	61	52	1962	3119	38598
Feb-15	53	43	65	56	1108	2779	36333
Mar-15	60	50	72	75	1587	2795	37025
Apr-15	65	58	74	65	1988	3420	42241
May-15	74	64	83	66	1683	3360	42425
Jun-15	80	68	90	74	1613	3419	40756
Jul-15	83	72	91	75	1176	2546	40889
Aug-15	82	73	90	74	1867	3675	41047
Sep-15	76	69	87	70	1745	2750	39771
Oct-15	67	55	80	71	1451	3210	40670
Nov-15	58	48	69	64	1590	3105	39180
Dec-15	52	42	62	62	1345	2653	35307
Jan-16	51	40	65	55	1561	2520	33115
Feb-16	53	46	66	58	1097	2669	32187
Mar-16	57	49	72	70	1254	2389	33123
Apr-16	66	58	77	69	2081	3380	36743
May-16	75	63	85	70	1195	3269	33768
Jun-16	82	70	89	70	1880	3018	37289
Jul-16	86	72	95	78	962	3037	37252
Aug-16	84	71	90	80	1571	3239	40433
Sep-16	78	70	85	72	1492	2316	33929