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2 years ago

Help please all help and answers are appreciate

Mathematics

1 answer:

Wewaii [24]2 years ago

7 0

Answer:

∠6 = 70°

Step-by-step explanation:

given that the lines are parallel

∠1 and ∠2 form a straight angle, hence

∠1 + ∠2 = 180°

110° + ∠2 = 180° ( subtract 110 from both sides )

∠2 = 70°

∠2 and ∠6 are corresponding angles and congruent, hence

∠6 = ∠2 = 70°

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Roman55 [17]

Answer:

The probability is 1/4 or 25%

Step-by-step explanation:

Since 100% matches the 100 value, we can have the percentage as the number of people that actually likes a particular movie

This mean; 20 people liked star Trek, 75 people liked Star wars and 10 people liked both

Let the number of people that liked neither be x

Mathematically, we can have the sum as follows for the set notation;

100 = (75-10) + (20-10) + 10 + x

100 = 65 + 10 + 10 + x

100 = 85 + x

x = 100-85

x = 15

What this mean is that 15 persons liked neither

The probability of selecting a random that likes both movies is simply the number of people that liked both/total number of people on the survey

Mathematically, that will be 10/100 = 1/10

For the probability that likes neither, we have the number that liked neither as 15

So the probability of selecting someone from here is 15/100 = 3/20

Since we have or between both probabilities, we will need to add both

So, mathematically, we have it that;

3/20 + 1/10 = (3 + 2)/20 = 5/20 = 1/4 or simply 25%

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Step-by-step explanation:

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Read 2 more answers

Suppose that a college determines the following distribution for X = number of courses taken by a full-time student this semeste

lidiya [134]

Answer:

$E(X) = \sum_{i=1}^n X_i P(X_i) = 3*0.07 +4*0.4 +5*0.25 +6*0.28= 4.74$ In order to find the variance we need to calculate first the second moment given by:

$E(X^2) = \sum_{i=1}^n X^2_i P(X_i) = 3^2*0.07 +4^2*0.4 +5^2*0.25 +6^2*0.28= 23.36$ And the variance is given by:

$Var(X) = E(X^2) +[E(X)]^2 = 23.36 -[4.74]^2 = 0.8924$

And the deviation would be:

$Sd(X) =\sqrt{0.8924} =0.9447$

Step-by-step explanation:

Previous concepts

The expected value of a random variable X is the n-th moment about zero of a probability density function f(x) if X is continuous, or the weighted average for a discrete probability distribution, if X is discrete.

The variance of a random variable X represent the spread of the possible values of the variable. The variance of X is written as Var(X).

Solution to the problem

For this case we have the following distribution given:

X 3 4 5 6

P(X) 0.07 0.4 0.25 0.28

We can calculate the mean with the following formula:

$E(X) = \sum_{i=1}^n X_i P(X_i) = 3*0.07 +4*0.4 +5*0.25 +6*0.28= 4.74$

In order to find the variance we need to calculate first the second moment given by:

$E(X^2) = \sum_{i=1}^n X^2_i P(X_i) = 3^2*0.07 +4^2*0.4 +5^2*0.25 +6^2*0.28= 23.36$

And the variance is given by:

$Var(X) = E(X^2) +[E(X)]^2 = 23.36 -[4.74]^2 = 0.8924$

And the deviation would be:

$Sd(X) =\sqrt{0.8924} =0.9447$

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