Answer:
56
Step-by-step explanation:
Given that there are 8 candidates for student government: Hal, Mary, Ann, Frank, Beth, John, Emily, and Tom.
The three candidates that receive the highest number of votes become candidates for a runoff election.
i.e. 3 persons out of 8 to be selected for becoming candidates for a runoff election.
Since order does not matter we use combinations here
3 persons out of 8 can be done in 8C3 ways
= 56
no of 3-candidate combinations possible are 56
the independent variable is the $6 you make at your job.
The dependent variable is how much you make each week. and the dependent variable represents x.
a reasonable domain for the function is going to have to be your $6 dollars because your pay rate doesn't go up or down.
a reasonable range for the function is 240 because you are only allowed to work 40 hours a week at any job unless they want to give you overtime so the max amount you can earn is $240
the function represents you working 20 hours and getting paid $120 because 6 times 20 is 120
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Log base3 (6*13.5)
log base 3 (81)
log base 3 (3)^4
4 log base 3 (3)
4 * 1 = 4
First condense the logs by using the product rule.
Next rewrite 81 in terms of 3.
Use the power rule and bring the 4 to the front.
log base 3 (3) = 1
Which leaves 4 * 1 = 4
Answer:
a = 4, b = 3
Step-by-step explanation:
Expand and simplify the given expression then compare coefficients of like terms.
a(bx + 5) - 2(bx + a)
= abx + 5a - 2bx - 2a
= (ab - 2b)x + 3a
Given that this expression is equal to 6x + 12
Comparing coefficients of like terms.
3a = 12 ( divide both sides by 3 )
a = 4
ab - 2b = 6 , that is
4b - 2b = 6
2b = 6 ( divide both sides by 2 )
b = 3
Thus a = 4 and b = 3
The linear regression method seeks to predict values of a(n) dependent variable based on values of a(n) independent variable.
According to the statement
we have to explain the linear regression method and explain the way by which this method is used to predict the values.
So, For this purpose we know that the
Linear regression is the most basic and commonly used predictive analysis. Regression estimates are used to describe data and to explain the relationship.
And
Linear regression analysis is used to predict the value of a variable based on the value of another variable. The variable you want to predict is called the dependent variable. The variable you are using to predict the other variable's value is called the independent variable.
from these definitions it is clear that the there is a presence of two types of variables which are dependent and independent variables.
So, The linear regression method seeks to predict values of a(n) dependent variable based on values of a(n) independent variable.
Learn more about Linear regression here brainly.com/question/25987747
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