Answer: see proof below
Step-by-step explanation:
Use the following identities
tan (A + B) = (tan A + tan B)/(1 - tan A · tan B) -->
tan 60° = √3
tan 120° = -√3
tan 3A = (3tanA - tan³A)/(1 - 3 tan²A) -->
Proof LHS → RHS
Given: tan Ф + tan(60° + Ф) + tan(120° + Ф)
Sum Difference: tan Ф + (tan 60° + tanФ)/(1-tan60°·tanФ) + (tan 120° + tanФ)/(1-tan120°·tanФ)
(latex)
Substitute: tan Ф + (√3 + tanФ)/(1-√3·tanФ) + (-√3 + tanФ)/(1+√3°·tanФ)
(latex)
Common Denominator: [tan Ф(1-3tan²Ф)+8tanФ]\(1-3tan²Ф)
(latex)
Distribute: (tan Ф - 3tan³Ф + 8Ф)\(1 - 3 tan²Ф)
(latex)
Simplify: (9Ф - 3tan³Ф)\(1 - 3 tan²Ф)
3(3Ф - tan³Ф)\(1 - 3 tan²Ф)
(latex)
Triple Angle Identity: 3 tan 3Ф
3 tan 3Ф = 3 tan 3Ф
Your question has been heard loud and clear.
tanθ+tan(60∘+θ)+tan(120∘+θ)
=tanθ+3–√+tanθ1−3–√tanθ+−3–√+tanθ1+3–√tanθ
[tanθ(1−3tan2θ)+(3–√+tanθ)(1+3–√tanθ)
=+(−3–√+tanθ)(1−3–√tanθ)1−3tan2θ
=9tanθ−3tan3θ1−3tan2θ=3tan3θ
Thank you.
Answer:
-5 IDS THE AANSERRRRR thanks
Step-by-step explanation:
Answer:
i can't do Graphs well but i am sure this will help
graph of the function f(x) = 2(x-3)f(x)=2(x−3) would generally look like:
The function f(x) = 2(x-3)f(x)=2(x−3) is a linear function in the form of y = mx + by=mx+b, where mm is the slope and bb is the y-intercept.
In this case, the slope mm is 2, which means that for every 1 unit increase in xx, yy will increase by 2 units. The fact that the slope is positive indicates that the graph will slant upwards from left to right.
The term (x-3)(x−3) represents a horizontal shift of the graph. When x = 3x=3, f(x) = 0f(x)=0, which means the graph crosses the y-axis at the point (3, 0).
Putting it all together, you can draw a line that passes through the point (3, 0) and slopes upward at an angle of approximately 45 degrees. The line will get steeper as it moves to the right. This graph represents the linear function f(x) = 2(x-3)f(x)=2(x−3).
Remember, you can use graphing tools or calculators to visualize and draw this function accurately.
Answer:
A conditional probability of an event is a probability obtained with knowledge that some other event has already occurred.
Step-by-step explanation:
Conditional probability of an event (A) is a probability obtained with knowledge that some other event (B) has already occurred and is denoted as P(A|B).
It satisfies the following equation:
where P(A and B) is the probability of A and B occurring together.
Conditional probability is applied in many areas of Bayesian statistics and machine learning.
The blank space should be filled with 'conditional'. A conditional probability of an event is a probability calculated with the knowledge that another event has already happened.
The blank space should be filled with 'conditional'. A conditional probability of an event is a probability obtained with knowledge that some other event has already occurred. Suppose you have events A and B from the same sample space. The conditional probability of event A given that event B has occurred, denoted as P(A|B), is computed as P(A and B) divided by P(B), where P(A and B) represents the probability that both events happen, and P(B) is the probability of B happening. This quantity is meaningful as long as P(B) is not zero.
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