Download the Costs of Production data set in Excel. Note the Units of Production (labeled Production) in Column B and the Total Costs (labeled Cost) by week.

Required

a. Perform a regression analysis with Cost as the dependent (outcome) variable and Production as the independent variable.

b. Estimate the adjusted R-square and Model F statistic of the regression output to assess the model fit.

c. Using the regression parameters, estimate the level of fixed costs overall and the variable costs overall.

 

Production data set 

Week beginning	Production	Cost
01-01-24	90879.85	60581
08-01-24	92861.62	61164
15-01-24	88266.54	47439
22-01-24	102707.1	63805
29-01-24	98902.95	50680
05-02-24	100824.5	54029
12-02-24	96341.31	62131
19-02-24	98627.49	48531
26-02-24	101557.4	59704
04-03-24	99439.44	59405
11-03-24	103840.7	51458
18-03-24	107099.2	61877
25-03-24	99582.59	48780
01-04-24	98861.93	58815
08-04-24	100150.6	54549
15-04-24	99606.91	55246
22-04-24	97893.52	56333
29-04-24	95741.57	61314
06-05-24	94683.82	49310
13-05-24	92791.83	54253
20-05-24	95758.64	62988
27-05-24	91928.85	57065
03-06-24	92030.74	45278
10-06-24	89155.85	55866
17-06-24	87079.55	57453
24-06-24	86325.63	47818
01-07-24	88610.16	56971
08-07-24	85315.53	50452
15-07-24	82184.08	47596
22-07-24	70991.73	45031
29-07-24	62346.86	34201
05-08-24	66241.21	38413
12-08-24	64520.41	32162
19-08-24	50829.65	28807
26-08-24	52881.67	32061
02-09-24	58668.45	35362
09-09-24	56668.71	33550
16-09-24	53890.9	30729
23-09-24	49113.1	32133
30-09-24	40871.27	27614
07-10-24	42188.16	30643
14-10-24	41478.53	27838
21-10-24	39506.4	23408
28-10-24	40419.03	26690
04-11-24	38302.7	27269
11-11-24	39770.68	27254
18-11-24	40039.12	24319
25-11-24	45984.73	28428
02-12-24	47916.62	30280
09-12-24	52572.86	33203
16-12-24	66529.59	37448
23-12-24	75288.2	49392