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4) Below is the graph of daily sales in thousands of dollars for the first 6.5 months that a product is on the market. 0 corresponds to Jan. 1 2017, so 6 corresponds to July 1 2017. M thousands of dollars 20 Daily sales 15 in 10 Time in months a) Approximate the date where daily sales are increasing the fastest. b) Estimate how quickly daily sales are increasing on that date. c) Approximate the date where daily sales are decreasing the fastest. d) Estimate how quickly daily sales are decreasing on that date.

4) Below is the graph of daily sales in thousands of dollars for the first 6.5 months that a product is on the market. 0 corresponds to Jan. 1 2017, so 6 corresponds to July 1 2017. M thousands of dollars 20 Daily sales 15 in 10 Time in months a) Approximate the date where daily sales are increasing the fastest. b) Estimate how quickly daily sales are increasing on that date. c) Approximate the date where daily sales are decreasing the fastest. d) Estimate how quickly daily sales are decreasing on that date.

Advanced Engineering Mathematics
Advanced Engineering Mathematics
10th Edition
ISBN:9780470458365
Author:Erwin Kreyszig
Publisher:Erwin Kreyszig
Chapter2: Second-order Linear Odes
Section: Chapter Questions
Problem 1RQ
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4) Below is the graph of daily sales in thousands of dollars for the first 6.5 months that a product is on the market. 0 corresponds to Jan. 1 2017, so 6 corresponds to July 1 2017. M thousands of dollars 20 Daily sales 15 in 10 Time in months a) Approximate the date where daily sales are increasing the fastest. b) Estimate how quickly daily sales are increasing on that date. c) Approximate the date where daily sales are decreasing the fastest. d) Estimate how quickly daily sales are decreasing on that date.
Transcribed Image Text:4) Below is the graph of daily sales in thousands of dollars for the first 6.5 months that a product is on the market. 0 corresponds to Jan. 1 2017, so 6 corresponds to July 1 2017. M thousands of dollars 20 Daily sales 15 in 10 Time in months a) Approximate the date where daily sales are increasing the fastest. b) Estimate how quickly daily sales are increasing on that date. c) Approximate the date where daily sales are decreasing the fastest. d) Estimate how quickly daily sales are decreasing on that date.
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