Answer:
14
Step-by-step explanation:
Given that:
Cost of purchase and installation = 5323.50
Cost per window = 230.25
Cost of installation = 2100
Hence,
Total purchase cost of windows alone :
5323.50 - 2100 = 3,223.50
Therefore, the number of windows purchased is :
(Total purchase cost of windows alone / price per window)
(3,223.50 / 230.25)
= 14
Hence, 14 windows was purchased
Answer:
f(-3) = -12
g(-2) = -19
General Formulas and Concepts:
<u>Pre-Algebra</u>
Order of Operations: BPEMDAS
- Brackets
- Parenthesis
- Exponents
- Multiplication
- Division
- Addition
- Subtraction
<u>Algebra I</u>
- Functions
- Function Notation
Step-by-step explanation:
<u>Step 1: Define</u>
<em>Identify</em>
f(x) = 3x - 3
g(x) = 3x³ + 5
f(-3) is <em>x</em> = -3 for function f(x)
g(-2) is <em>x</em> = -2 for function g(x)
<u>Step 2: Evaluate</u>
f(-3)
- Substitute in <em>x</em> [Function f(x)]: f(-3) = 3(-3) - 3
- Multiply: f(-3) = -9 - 3
- Subtract: f(-3) = -12
g(-2)
- Substitute in <em>x</em> [Function g(x)]: g(-2) = 3(-2)³ + 5
- Exponents: g(-2) = 3(-8) + 5
- Multiply: g(-2) = -24 + 5
- Add: g(-2) = -19
This question is incomplete, the complete question is;
Suppose John is a high school statistics teacher who believes that watching many hours of TV leads to lower test scores. Immediately after giving the most recent test, he surveyed each of the 24 students in his class and asked them how many hours of TV they watched that week. He then matched each student's test grade with his or her survey response. After compiling the data, he used hours of TV watched to predict each student's test score. He found the least-squares regression line to be y" = -1.5x + 85.
He also calculated that the value of r, the correlation, was -0.61.
what is the correct value of the coefficient of determination R² and give a correct interpretation of its meaning
Answer:
Interpretation of coefficient of determination R² = 0.3721
R² = 0.3721, meaning 37.21% of the total variation in test scores can be explained by the least square regression line
Step-by-step explanation:
Given the data in the question;
the least square regression line is;
y" = -1.5x + 85
the correlation coefficient r = -0.61
Now, the coefficient of determination R² is square of correlation coefficient r
R² = -61²
R² = 0.3721
Answer:
3160
Step-by-step explanation:
3.16 x 10^3
10^3 = 1000
so you move the decimal point three times to the right
I hope this helps
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