There is 7,000 female students, and 5,000 male students. Because, if there was 2,000 more female students then male, you have to find out what two numbers add up to 12,000. (Tip, to make it easier, take away the thousands, like 7+5)
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This is a rectangular prism. Its volume is V = (length)(width)(height).
Here, V = (10 cm)(3 cm)(2 cm) = 60 cm^3.
Answer:
-0.20
Step-by-step explanation:
Given the data:
Age at auction (x) ____price sold (y)
391
51
32
84
47
104
88
43
470
51
Y:
76.9
95.4
86.3
49.3
80
57
47.8
80
70
86.9
General formula for a simple linear regression :
y = ab + c
Where ;
y = predicted variable ; a = slope / gradient
b = predictor / independent variable ; c = intercept
From the result obtained from the calculator :
y = -0.01246X + 74.65552
Correlation Coefficient is used to measure the strength of relationship between linear variables.
The regression Coefficient obtained is - 0.20
This shows that there is a weak negative correlation between the age at auction and the price at which painting is sold. This is because the negative sign means that value of y decreases as x increases or vice versa, however, due to a correlation vale which is closer to 0 than 1 or - 1, we can conclude that the negative relationship between the variables is weak.
Let us say that:
x = cost of shorts
y = cost of slacks
z = cost of sports coat
From the given statements, we can create the following
equations:
eqtn 1: 3 x + y =
10.96
eqtn 2: 7 x + 2 y +
z = 30.40
eqtn 3: 4 x + z =
14.45
Rewrite eqtn 1 explicit to y:
y = 10.96 – 3 x -->
eqtn 4
Rewrite eqtn 3 explicit to z:
z = 14.45 – 4x -->
eqtn 5
Plug in the values of y (eqtn 4) and z (eqtn 5) to eqtn
2:
7 x + 2 (10.96 – 3 x) + 14.45 – 4 x = 30.40
7 x + 21.92 – 6 x + 14.45 – 4 x = 30.40
- 3 x + 36.37 = 30.40
- 3 x = - 5.97
x = 1.99
Eqtn 4:
y = 10.96 – 3 x
y = 10.96 – 3 (1.99)
y = 4.99
Eqtn 5:
z = 14.45 – 4x
z = 14.45 – 4 (1.99)
z = 6.49
Therefore each shirt cost $1.99, each slacks cost $4.99,
and each sports coat cost $6.49.
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