(Y – Y) | (X – X)(Y – Y)| (X – X)² 35.00 Price (X) Sales (Y) (X – X). 100.0 -0.70 Y – Y)² - 1.30 -24.50 0.49 1225 1.60 90.0 -0.4 25.0 -10.00 0.16 625 1.80 90.0 -0.20 25.00 -5.00 0.04 625 2.00 40.0 0.00 -25.00 0.00 0.00 625 2.40 38.0 0.40 -27.00 -10.80 0.16 729 2.90 32.0 0.90 -33.00 -29.70 0.81 1089 12.00 390.0 -80.00 1.66 4918.00

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A candy bar manufacturer is interested in trying to estimate how sales are influenced by the price of
their product. To do this, the company randomly chooses 6 small cities and offers the candy bar at
different prices. What is the correlation between candy price and sales?
City
Price ($)
Sales
Miami
1.30
100
McKinney
1.60
90
Newberg
1.80
90
Prescott
2.00
40
Таcoma
2.40
38
San Jose
2.90
32
Price (X) Sales (Y)
(Ү — Ү) | (X — ХY -Y)| (X — X)2
35.00
kY – Y)²
2
(X – X)
100.0
1.30
-0.70
-24.50
0.49
1225
1.60
90.0
-0.4
25.0
-10.00
0.16
625
1.80
90.0
-0.20
25.00
-5.00
0.04
625
2.00
40.0
0.00
-25.00
0.00
0.00
625
2.40
38.0
0.40
-27.00
-10.80
0.16
729
2.90
32.0
0.90
-33.00
-29.70
0.81
1089
otal
12.00
390.0
-80.00
1.66
4918.00
Transcribed Image Text:A candy bar manufacturer is interested in trying to estimate how sales are influenced by the price of their product. To do this, the company randomly chooses 6 small cities and offers the candy bar at different prices. What is the correlation between candy price and sales? City Price ($) Sales Miami 1.30 100 McKinney 1.60 90 Newberg 1.80 90 Prescott 2.00 40 Таcoma 2.40 38 San Jose 2.90 32 Price (X) Sales (Y) (Ү — Ү) | (X — ХY -Y)| (X — X)2 35.00 kY – Y)² 2 (X – X) 100.0 1.30 -0.70 -24.50 0.49 1225 1.60 90.0 -0.4 25.0 -10.00 0.16 625 1.80 90.0 -0.20 25.00 -5.00 0.04 625 2.00 40.0 0.00 -25.00 0.00 0.00 625 2.40 38.0 0.40 -27.00 -10.80 0.16 729 2.90 32.0 0.90 -33.00 -29.70 0.81 1089 otal 12.00 390.0 -80.00 1.66 4918.00
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