I received the linear regression results and know that the demand function is Q 39 057 2 461(Price) We are also given this chart Price Number of Subscribers (Thousands) Cost of License Fees (Thousands) Divisional Sales, General and Administrative Costs (Thousands) Total Revenue Price x Number of Subcribers (Thousands) Total Cost Cost of License Div Sales, Gen, and Admin Costs (Thousands) Profit TR TC (Thousands) $5 00 29 974 $134 88 $14 50 $149 87 $149 38 $0 49 $5 50 29 256 $131 65 $14 50 $160 91 $146 15 $14 76 $6 00 17 822 $80 20 $14 50 $106 93 $94 70 $12 23 $6 50 22 657 $101 96 $14 50 $147 27 $116 46 $30 81 $7 00 19 897 $89 54 $14 50 $139 28 $104 04 $35 24 $7 50 16 671 $75 02 $14 50 $125 03 $89 52 $35 51 $8 00 20 492 $92 21 $14 50 $163 93 $106 71 $57 22 $8 50 20 000 $90 00 $14 50 $170 00 $104 50 $65 50 $9 00 19 760 $88 92 $14 50 $177 84 $103 42 $74 42 $9 50 17 123 $77 05 $14 50 $162 67 $91 55 $71 11 $10 00 12 644 $56 90 $14 50 $126 44 $71 40 $55 04 $10 50 12 785 $57 53 $14 50 $134 24 $72 03 $62 21 $11 00 12 216 $54 97 $14 50 $134 38 $69 47 $64 91 We are told that the current product sells for $9 75 month, that there are 15,059 subscribers and revenue is 146,823 We are asked to estimate price sensitivity at the current price and determine how low product should be price along with the potential revenue using the DEMAND EQUATION which is Q 39 057 2 461(Price) from the linear regression ran on our data

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Posted on Sep 18, 2020

I received the linear regression results and know that the demand function is Q = 39.057 2.461(Price). We are also given this chart- Price

I received the linear regression results and know that the demand function is Q = 39.057 – 2.461(Price). We are also given this chart-

Price	Number of Subscribers (Thousands)	Cost of License Fees (Thousands)	Divisional Sales, General and Administrative Costs (Thousands)	Total Revenue = Price x Number of Subcribers -(Thousands)	Total Cost = Cost of License + Div. Sales, Gen, and Admin. Costs (Thousands)	Profit = TR-TC (Thousands)
$5.00	29.974	$134.88	$14.50	$149.87	$149.38	$0.49
$5.50	29.256	$131.65	$14.50	$160.91	$146.15	$14.76
$6.00	17.822	$80.20	$14.50	$106.93	$94.70	$12.23
$6.50	22.657	$101.96	$14.50	$147.27	$116.46	$30.81
$7.00	19.897	$89.54	$14.50	$139.28	$104.04	$35.24
$7.50	16.671	$75.02	$14.50	$125.03	$89.52	$35.51
$8.00	20.492	$92.21	$14.50	$163.93	$106.71	$57.22
$8.50	20.000	$90.00	$14.50	$170.00	$104.50	$65.50
$9.00	19.760	$88.92	$14.50	$177.84	$103.42	$74.42
$9.50	17.123	$77.05	$14.50	$162.67	$91.55	$71.11
$10.00	12.644	$56.90	$14.50	$126.44	$71.40	$55.04
$10.50	12.785	$57.53	$14.50	$134.24	$72.03	$62.21
$11.00	12.216	$54.97	$14.50	$134.38	$69.47	$64.91

We are told that the current product sells for $9.75 / month, that there are 15,059 subscribers and revenue is 146,823.

We are asked to estimate price sensitivity at the current price and determine how low product should be price along with the potential revenue using the DEMAND EQUATION which is Q = 39.057 – 2.461(Price) from the linear regression ran on our data.