Question

Multiple Regression Analysis was used to find out which X variable have relationship with my Y variable (reduce overspending on food and beverage), and how strong relationship is.FIT A FIRST ORDER AUTO AGGRESSIVE MODEL (AR(1) USING Y(T) AS THE RESPONSE VARIABLE Y (T-1) AS THE INPUT VARIABLE. RECORD THE REGRESSION EQUATION.

CALCULATE THE EXPONENTIAL SMOOTHING MODELS AND CALCULATE A MOVING AVERAGE MODEL.

2/1/2019	59.73
2/1/2019	71.58
2/1/2019	29.35
2/1/2019	18.81
2/2/2019	2.66
2/2/2019	2.66
2/4/2019	21.73
2/4/2019	33.65
2/5/2019	57.48
2/5/2019	24.00
2/9/2019	63.15
2/10/2019	8.99
2/11/2019	33.10
2/11/2019	9.10
2/12/2019	4.67
2/12/2019	23.30
2/12/2019	38.40
2/13/2019	5.53
2/13/2019	18.95
2/15/2019	83.05
2/19/2019	10.32
2/19/2019	4.67
2/21/2019	3.10
2/21/2019	29.83
2/22/2019	63.36
2/22/2019	68.16
2/22/2019	7.99
2/22/2019	29.31
2/22/2019	68.10
2/23/2019	27.69
2/25/2019	287.68
2/25/2019	34.16
2/26/2019	8.89
2/27/2019	61.44
3/1/2019	7.30
3/1/2019	6.60
3/1/2019	2.61
3/1/2019	24.66
3/4/2019	117.42
3/4/2019	11.71
total:	1484.89

Answer 1

Time series plot day1y yi-mean (y)-37.122 T:-length (g) -40 Sample mean: 159.73 2 71.58 3 29.35 4 18.81 5 2.66 6 2.66 7 21.73 8 33.65 9 57.48 10 24 11 63.15 300 240 210 180 150 120 90- 60 30 0 9 13 21 25 37 41 day

12 8.99 13 33.1 14 9.1 15 4.67 16 23.3 17 38.4 18 5.53 19 18.95 20 83.05 21 10.32 22 4.67 233.1 T-k t+k 93288.4141 e ((*-·-).(*.k-,-),--1768.0787 The sample ACF at lag k-1 -0.019 The sample ACF at lag k:-2,3..T-1 0

25 63.36 26 68.16 27 7.99 28 29.31 2968.1 30 27.69 31 287.68 32 34.16 338.89 34 61.44 35 7.3 36 6.6 37 2.61 The sample ACF at lag k:-2,3..T-1 61 4.5 3 1.5 16 26.5 30 1.5 -4.5 7.5

Time series plot of 5 period moving average 40 11.71 -5 n:= length (y)-40 M: Forecasting using Exponsential smoothening method forecasting ofy: 0 W:-0.25 T-1

300 0 5 9 13 17 21 29 37 41 day