Quantitative Analysis Of Business Performance

Movie_ID	Radio_Adv	TV_Adv	Newspaper_Adv	Screen_Weeks	Theatre_Type	Sales (1000$)
1	56	16	1	12	Lux	$ 4,015
2	28	7	1	7	Regular	$ 2,055
3	46	19	1	7	Xtreme	$ 2,608
4	82	30	2	9	Regular	$ 2,987
5	53	26	1	6	Regular	$ 2,619
6	89	36	0	7	Lux	$ 3,916
7	58	18	2	12	Xtreme	$ 3,395
8	113	47	2	7	Regular	$ 3,785
9	14	4	1	6	Lux	$ 2,017
10	29	1	1	10	Regular	$ 2,348
11	69	21	2	9	Lux	$ 3,940
12	99	26	1	11	Regular	$ 3,732
13	144	63	1	8	Regular	$ 4,578
14	124	55	2	12	Lux	$ 5,800
15	76	35	1	12	Regular	$ 3,938
16	49	16	1	9	Regular	$ 2,931
17	10	1	1	11	Lux	$ 3,009
18	116	37	3	6	Regular	$ 3,566
19	130	53	1	11	Lux	$ 5,691
20	30	3	1	11	Xtreme	$ 2,295
21	100	47	3	9	Xtreme	$ 4,027
22	91	33	3	11	Regular	$ 4,120
23	49	17	0	6	Regular	$ 2,437
24	27	11	2	10	Regular	$ 2,174
25	108	43	1	9	Xtreme	$ 3,878
26	30	12	2	6	Regular	$ 2,021
27	81	35	0	6	Regular	$ 3,133
28	96	36	1	10	Regular	$ 4,026
29	16	5	1	11	Regular	$ 2,128
30	85	34	0	11	Xtreme	$ 3,658
31	95	33	2	8	Regular	$ 3,609
32	64	13	0	6	Regular	$ 2,139
33	82	16	1	8	Xtreme	$ 2,921
34	72	30	0	11	Xtreme	$ 3,640
35	37	14	1	11	Regular	$ 3,055
36	47	21	1	8	Regular	$ 2,659
37	69	19	2	11	Regular	$ 3,095
38	95	42	0	7	Lux	$ 3,954
39	20	8	2	6	Regular	$ 1,785
40	98	43	4	11	Xtreme	$ 4,241
41	84	38	1	12	Xtreme	$ 4,311
42	39	7	3	6	Lux	$ 2,318
43	79	37	2	9	Lux	$ 4,370
44	61	22	1	7	Regular	$ 2,350
45	78	35	0	10	Regular	$ 3,637
46	50	22	2	6	Regular	$ 2,390
47	3	1	1	6	Regular	$ 1,362
48	56	26	1	6	Lux	$ 3,266
49	33	15	0	8	Regular	$ 2,709
50	53	10	2	9	Lux	$ 3,206
51	120	58	1	9	Regular	$ 4,842
52	117	39	1	9	Xtreme	$ 3,870
53	27	11	1	9	Regular	$ 2,477
54	31	4	2	10	Regular	$ 2,280
55	61	26	0	11	Regular	$ 3,288
56	78	21	1	6	Lux	$ 3,460
57	143	60	1	6	Regular	$ 4,418
58	36	11	1	8	Xtreme	$ 2,392
59	70	27	1	11	Regular	$ 3,331
60	82	19	0	9	Regular	$ 3,366
61	144	56	0	6	Lux	$ 4,919
62	83	40	1	10	Xtreme	$ 3,860
63	86	38	1	6	Xtreme	$ 3,117
64	13	5	0	10	Regular	$ 2,364
65	56	25	1	11	Xtreme	$ 3,394
66	46	20	0	11	Regular	$ 3,024
67	76	14	0	7	Regular	$ 3,201
68	91	38	2	10	Xtreme	$ 3,789
69	129	57	2	12	Regular	$ 5,025
70	117	40	0	9	Regular	$ 3,950
71	108	36	2	10	Xtreme	$ 4,020
72	45	20	2	9	Regular	$ 2,447
73	45	10	0	7	Lux	$ 2,913
74	110	37	0	7	Lux	$ 4,085
75	113	48	1	9	Regular	$ 4,195
76	91	41	1	7	Xtreme	$ 3,402
77	92	38	1	9	Xtreme	$ 3,778
78	63	5	2	8	Xtreme	$ 2,050
79	100	30	2	6	Regular	$ 3,430
80	115	56	2	8	Xtreme	$ 4,344
81	111	54	0	9	Regular	$ 4,155
82	140	59	3	10	Regular	$ 4,805
83	75	33	1	7	Lux	$ 3,498
84	73	36	0	11	Lux	$ 4,009
85	93	40	2	9	Xtreme	$ 3,700
86	88	28	2	11	Xtreme	$ 3,678
87	123	44	1	6	Regular	$ 3,782
88	49	19	0	12	Lux	$ 4,085
89	37	3	2	11	Regular	$ 2,421
90	187	82	2	7	Regular	$ 5,539
91	32	6	1	10	Regular	$ 2,469
92	117	56	1	6	Lux	$ 4,408
93	17	4	1	8	Regular	$ 1,962
94	89	33	1	12	Xtreme	$ 3,978
95	111	39	2	7	Regular	$ 3,814
96	137	65	2	7	Lux	$ 5,501
97	91	24	3	6	Lux	$ 3,299
98	106	38	0	11	Regular	$ 3,807
99	67	17	1	9	Lux	$ 3,315
100	93	34	0	11	Lux	$ 4,379
101	172	59	3	10	Lux	$ 5,885
102	60	20	1	12	Lux	$ 4,329
103	39	8	2	9	Regular	$ 2,523
104	36	16	2	6	Regular	$ 1,799
105	143	71	2	6	Regular	$ 4,420
106	20	3	1	10	Lux	$ 3,185
107	63	24	3	12	Xtreme	$ 3,287
108	65	18	2	7	Xtreme	$ 2,650
109	50	20	1	10	Lux	$ 3,843
110	105	49	0	9	Lux	$ 4,893
111	137	64	2	8	Regular	$ 5,005
112	86	36	2	9	Regular	$ 3,775
113	45	19	3	10	Xtreme	$ 3,134
114	95	43	1	9	Regular	$ 3,563
115	98	38	3	9	Lux	$ 4,382
116	138	64	0	11	Regular	$ 5,048
117	31	8	1	6	Lux	$ 2,195
118	28	3	1	11	Regular	$ 2,621
119	97	44	1	8	Regular	$ 3,784
120	91	38	2	6	Regular	$ 3,351

Project 1: Cinematographia – Multiple regression
Movie_ID	Radio_Adv	TV_Adv	Newspaper_Adv	Screen_Weeks	Sales (1000$)					Correlation Matrix
1	56	16	1	12	4,015					Radio_Adv	TV_Adv	Newspaper_Adv	Screen_Weeks	Sales (1000$)
2	28	7	1	7	2,055				Radio_Adv	1.000	0.940	0.128	-0.056	0.865
3	46	19	1	7	2,608				TV_Adv	0.940	1.000	0.092	-0.049	0.866
4	82	30	2	9	2,987				Newspaper_Adv	0.128	0.092	1.000	-0.017	0.064
5	53	26	1	6	2,619				Screen_Weeks	-0.056	-0.049	-0.017	1.000	0.265
6	89	36	0	7	3,916				Sales (1000$)	0.865	0.866	0.064	0.265	1.000
7	58	18	2	12	3,395
8	113	47	2	7	3,785
9	14	4	1	6	2,017
10	29	1	1	10	2,348
11	69	21	2	9	3,940
12	99	26	1	11	3,732
13	144	63	1	8	4,578
14	124	55	2	12	5,800
15	76	35	1	12	3,938
16	49	16	1	9	2,931
17	10	1	1	11	3,009
18	116	37	3	6	3,566
19	130	53	1	11	5,691
20	30	3	1	11	2,295
21	100	47	3	9	4,027
22	91	33	3	11	4,120
23	49	17	0	6	2,437
24	27	11	2	10	2,174
25	108	43	1	9	3,878
26	30	12	2	6	2,021
27	81	35	0	6	3,133
28	96	36	1	10	4,026
29	16	5	1	11	2,128
30	85	34	0	11	3,658
31	95	33	2	8	3,609
32	64	13	0	6	2,139
33	82	16	1	8	2,921
34	72	30	0	11	3,640
35	37	14	1	11	3,055
36	47	21	1	8	2,659
37	69	19	2	11	3,095
38	95	42	0	7	3,954
39	20	8	2	6	1,785
40	98	43	4	11	4,241
41	84	38	1	12	4,311
42	39	7	3	6	2,318
43	79	37	2	9	4,370
44	61	22	1	7	2,350
45	78	35	0	10	3,637
46	50	22	2	6	2,390
47	3	1	1	6	1,362
48	56	26	1	6	3,266
49	33	15	0	8	2,709
50	53	10	2	9	3,206
51	120	58	1	9	4,842
52	117	39	1	9	3,870
53	27	11	1	9	2,477
54	31	4	2	10	2,280
55	61	26	0	11	3,288
56	78	21	1	6	3,460
57	143	60	1	6	4,418
58	36	11	1	8	2,392
59	70	27	1	11	3,331
60	82	19	0	9	3,366
61	144	56	0	6	4,919
62	83	40	1	10	3,860
63	86	38	1	6	3,117
64	13	5	0	10	2,364
65	56	25	1	11	3,394
66	46	20	0	11	3,024
67	76	14	0	7	3,201
68	91	38	2	10	3,789
69	129	57	2	12	5,025
70	117	40	0	9	3,950
71	108	36	2	10	4,020
72	45	20	2	9	2,447
73	45	10	0	7	2,913
74	110	37	0	7	4,085
75	113	48	1	9	4,195
76	91	41	1	7	3,402
77	92	38	1	9	3,778
78	63	5	2	8	2,050
79	100	30	2	6	3,430
80	115	56	2	8	4,344
81	111	54	0	9	4,155
82	140	59	3	10	4,805
83	75	33	1	7	3,498
84	73	36	0	11	4,009
85	93	40	2	9	3,700
86	88	28	2	11	3,678
87	123	44	1	6	3,782
88	49	19	0	12	4,085
89	37	3	2	11	2,421
90	187	82	2	7	5,539
91	32	6	1	10	2,469
92	117	56	1	6	4,408
93	17	4	1	8	1,962
94	89	33	1	12	3,978
95	111	39	2	7	3,814
96	137	65	2	7	5,501
97	91	24	3	6	3,299
98	106	38	0	11	3,807
99	67	17	1	9	3,315
100	93	34	0	11	4,379
101	172	59	3	10	5,885
102	60	20	1	12	4,329
103	39	8	2	9	2,523
104	36	16	2	6	1,799
105	143	71	2	6	4,420
106	20	3	1	10	3,185
107	63	24	3	12	3,287
108	65	18	2	7	2,650
109	50	20	1	10	3,843
110	105	49	0	9	4,893
111	137	64	2	8	5,005
112	86	36	2	9	3,775
113	45	19	3	10	3,134
114	95	43	1	9	3,563
115	98	38	3	9	4,382
116	138	64	0	11	5,048
117	31	8	1	6	2,195
118	28	3	1	11	2,621
119	97	44	1	8	3,784
120	91	38	2	6	3,351

Removed Radio as it is highly correlated with TV ( and TV has more strong relationship with Sales than Radio)
Created dummy for Screen type , Luxury theatre has significant effect on Sales
Newspaper Ad are treated as categorical variables, hence 4 dummies are created, but none of the dummies are significant hence dropping the variable

SUMMARY OUTPUT

Regression Statistics
Multiple R	0.969462
R Square	0.939857
Adjusted R Square	0.938302
Standard Error	234.5438
Observations	120

ANOVA
	df	SS	MS	F	Significance F
Regression	3	99720552	33240184	604.2481483	0.00
Residual	116	6381255	55010.82
Total	119	1.06E+08

	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95.0%	Upper 95.0%
Intercept	589.3656	106.504	5.533742	0.0000	378.4210168	800.3102	378.421	800.3102
TV_Adv	45.81986	1.185338	38.65552	0.0000	43.47214416	48.16757	43.47214	48.16757
Screen_Weeks	155.4349	10.79537	14.39829	0.0000	134.0532707	176.8165	134.0533	176.8165
Lux_d1	665.6602	49.01853	13.57977	0.0000	568.5728002	762.7476	568.5728	762.7476


a) Which independent variable has the strongest linear relationship with sales?
Ans: Tv Ad has the strongest relationship with Sales ( based on the t value)

b) Is your multiple regression model overall significant?
Ans: Yes, it is significant as the p value for the overall model is significant

c) If so, which variables do not help you in modelling the dependent variable?
Ans: Newspaper ad was not helpful in predicting the sales

d) Once you’ve built your final model, are there any potential multi-collinearity problems? If so, which variables are they? (If there are collinearity problems between the independent measures, you should firstly remove the variable that has the “least correlation” with the dependent measure, then run the model and assess again).
Ans: Radio Ad & Tv Ad were highly correlated, so based on the correlation with Sales, Tv has been selected

e) How well does the model explain sales (use R2 in your explanation)?
Ans: The model is providing good explanation of the variation in sales ( it is explaining 93% of the variation)

f) What would be the sales for a movie with 50 radio ads per week, 40 TV ads per week, 2 newspaper ads per week, and which played for 2 weeks in a Lux Theatre? [Note, only use the values that you have found to be significant (α set at 0.05) contributors to the behaviour of the dependent measure].

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