Please help meee hbenekneje

Identifying functions from relations

Mashutka [201]

I don’t know but I need the Points sorry for you

4 0

2 years ago

What is 7/8 x 1/3 x 2/3? Pls help me.

Step2247 [10]

7/36
Multiply the top together and then the bottom together and the final numbers on top and bottom is your answer.

8 0

3 years ago

Read 2 more answers

How do I do This math....-2.5-(-3.25)=

zhannawk [14.2K]

When you subtract a negative, it changes it to adding a positive.

= -2.5 - (-3.25)

= -2.5 + 3.25

= 0.75

Hope This Helped! Good Luck!

3 0

3 years ago

2.5% of a population are infected with a certain disease. There is a test for the disease, however the test is not completely ac

Aleks04 [339]

Answer:

$P(disease/positivetest) = 0.36116$

Step-by-step explanation:

This is a conditional probability exercise.

Let's name the events :

I : ''A person is infected''

NI : ''A person is not infected''

PT : ''The test is positive''

NT : ''The test is negative''

The conditional probability equation is :

Given two events A and B :

P(A/B) = P(A ∩ B) / P(B)

$P(B) >0$

P(A/B) is the probability of the event A given that the event B happened

P(A ∩ B) is the probability of the event (A ∩ B)

(A ∩ B) is the event where A and B happened at the same time

In the exercise :

$P(I)=0.025$

$P(NI)= 1-P(I)=1-0.025=0.975\\P(NI)=0.975$

$P(PT/I)=0.904\\P(PT/NI)=0.041$

We are looking for P(I/PT) :

P(I/PT)=P(I∩ PT)/ P(PT)

$P(PT/I)=0.904$

P(PT/I)=P(PT∩ I)/P(I)

0.904=P(PT∩ I)/0.025

P(PT∩ I)=0.904 x 0.025

P(PT∩ I) = 0.0226

P(PT/NI)=0.041

P(PT/NI)=P(PT∩ NI)/P(NI)

0.041=P(PT∩ NI)/0.975

P(PT∩ NI) = 0.041 x 0.975

P(PT∩ NI) = 0.039975

P(PT) = P(PT∩ I)+P(PT∩ NI)

P(PT)= 0.0226 + 0.039975

P(PT) = 0.062575

P(I/PT) = P(PT∩I)/P(PT)

$P(I/PT)=\frac{0.0226}{0.062575} \\P(I/PT)=0.36116$

8 0

3 years ago

An analyst must decide between two different forecasting techniques for weekly sales of roller blades: a linear trend equation a

Amiraneli [1.4K]

Answer:

Following are the responses to the given question:

Step-by-step explanation:

Mean Absolute Deviation MAD

$MAD = \sum_{i=1}^{n} \frac{\left | actual_{i}-forecast_{i} \right |}{n}$

Mean squared error

$MSE=\Sigma^{n}_{i=1} \frac{(Actual_i - Forecast_i)^2}{(n - 1)}$

linear trend equation is $Ft = 124 + 2t$

$MAD = \frac{23}{10} = 2.3\\\\MSE = \frac{91}{9}= 10.11\\\\$

Naive method

$MAD = \frac{36}{9} = 4\\\\MSE = \frac{202}{8}=25.25\\\\MAD (Naive) = 4\\\\MAD (Linear) =2.3\\\\MSE (Naive)=25.25\\\\MSE (Linear)=10.11\\\\$

Please find the attached file.

7 0

3 years ago