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Topic 7 Homework (Nonadaptive)
Question 7 of 16 (1 point)**|**Question Attempt: 1 of Unlimited
Dennis
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Question 7
You are the owner of Fast Break, a popular local place that sells drinks, snacks, and sandwiches. For inventory management purposes, you are examining how the weather affects the amount of hot chocolate sold in a day. You are going to gather a random sample of
9
days showing that day's high temperature (denoted by
x
, in
°C
) and the amount of hot chocolate sold that day (denoted by
y
, in liters). You will also note the product
·xy
of the temperature and amount of hot chocolate sold for each day. (These products are written in the row labeled "
xy
").
(a)Click on "Take Sample" to see the results for your random sample.
Take Sample
High temperature,
x
(in
°C
)
12
18
23
7
29
12
23
3
15
Amount of hot chocolate sold,
y
(in liters)
10
7
11
16
5
15
8
18
12
xy
120
126
253
112
145
180
184
54
180
Send data to calculator
Based on the data from your sample, enter the indicated values in the column on the left below. Round decimal values to three decimal places. When you are done, select "Compute". (In the table below,
n
is the sample size and the symbol
Σxy
means the sum of the values
xy
.)
n
:
9
x
:
142
y
:
102
sx
:
1354
sy
:
2472
Σxy
:
1434
Compute
Sample correlation coefficient (
r
):
−0.005
Slope (
b1
):
−0.01
y
-intercept (
b0
):
103.25
(b)Write the equation of the least-squares regression line for your data. Then on the scatter plot for your data, graph this regression equation by plotting two points and then drawing the line through them. Round each coordinate to three decimal places.
Regression equation:
y
=
Amount of hot chocolate sold (in liters)
y
2
4
6
8
10
12
14
16
18
20
22
24
x
3
6
9
12
15
18
21
24
27
30
33
36
0
High temperature (in
°C
)
(c)Use your regression equation to predict the amount of hot chocolate sold on a day with a high temperature of
19 °C
. Round your answer to the nearest whole number.
Predicted amount of hot chocolate sold:
liters19
Check
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Math Problem Analysis
Mathematical Concepts
Statistics
Regression Analysis
Correlation
Linear Equations
Formulas
Sample correlation coefficient formula: r = (nΣxy - ΣxΣy) / sqrt{[nΣx² - (Σx)²][nΣy² - (Σy)²]}
Slope formula: b₁ = (nΣxy - ΣxΣy) / (nΣx² - (Σx)²)
Intercept formula: b₀ = ȳ - b₁x̄
Regression equation: ŷ = b₀ + b₁x
Theorems
Least Squares Regression Theorem
Suitable Grade Level
Grades 10-12
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