This is the question I don't understand

Opposites and absolute value mean the same thing. True or false

poizon [28]

Answer:

The absolute value of a number is the distance between the number and zero on a number line. In other words, a number and its opposite have the same absolute value.

Step-by-step explanation:

7 0

3 years ago

i know this isnt really a school question but i really need help... So recently i got a husky and at her old house we are thinki

Andrej [43]

Give highly palatable and nutritious food.
Make sure the food smells right.
If you're feeding your dog kibble, add some warm water, bone broth, or wet food.
Offer home-cooked food.
Cut down on treats and avoid feeding off the table.
Praise the dog for eating the food.

5 0

3 years ago

A dictionary contains the following 10 words: a, the, your, blue, red, purple, card, token, hat, shirt.

Serhud [2]

Answer:

0.1

Step-by-step explanation:

because the probability is 1 out of 10 so if you divide 1/10 it is equal to 0.1

8 0

3 years ago

Read 2 more answers

Lie detectors have a 15% chance of concluding that a person is lying even when they are telling the truth. a bank conducts inter

Otrada [13]

Part A:

Given that lie detectors have a 15% chance of concluding that a person is lying even when they are telling the truth. Thus, lie detectors have a 85% chance of concluding that a person is telling the truth when they are indeed telling the truth.

The case that the lie detector correctly determined that a selected person is saying the truth has a probability of 0.85
Thus p = 0.85

Thus, the probability that the lie detector will conclude that all 15 are telling the truth if all 15 applicants tell the truth is given by:

 $P(X)={ ^nC_xp^xq^{n-x}} \\ \\ \Rightarrow P(15)={ ^{15}C_{15}(0.85)^{15}(0.15)^0} \\ \\ =1\times0.0874\times1=0.0874$


Part B:

Given that lie detectors have a 15% chance of concluding that a person is lying even when they are telling the truth. Thus, lie detectors have a 85% chance of concluding that a person is telling the truth when they are indeed telling the truth.

The case that the lie detector wrongly determined that a selected person is lying when the person is actually saying the truth has a probability of 0.25
Thus p = 0.15

Thus, the probability that the lie detector will conclude that at least 1 is lying if all 15 applicants tell the truth is given by:

$P(X)={ ^nC_xp^xq^{n-x}} \\ \\ \Rightarrow P(X\geq1)=1-P(0) \\ \\ =1-{ ^{15}C_0(0.15)^0(0.85)^{15}} \\ \\ =1-1\times1\times0.0874=1-0.0874 \\ \\ =0.9126$

Part C:

Given that lie detectors have a 15% chance of concluding that a person is lying even when they are telling the truth. Thus, lie detectors have a 85% chance of concluding that a person is telling the truth when they are indeed telling the truth.

The case that the lie detector wrongly determined that a selected person is lying when the person is actually saying the truth has a probability of 0.15
Thus p = 0.15

The mean is given by:

$\mu=npq \\ \\ =15\times0.15\times0.85 \\ \\ =1.9125$

Part D:

Given that lie detectors have a 15% chance of concluding that a person is lying even when they are telling the truth. Thus, lie detectors have a 85% chance of concluding that a person is telling the truth when they are indeed telling the truth.

The case that the lie detector wrongly determined that a selected person is lying when the person is actually saying the truth has a probability of 0.15
Thus p = 0.15

The probability that the number of truthful applicants classified as liars is greater than the mean is given by:

 $P(X\ \textgreater \ \mu)=P(X\ \textgreater \ 1.9125) \\ \\ 1-[P(0)+P(1)]$

 $P(1)={ ^{15}C_1(0.15)^1(0.85)^{14}} \\ \\ =15\times0.15\times0.1028=0.2312$

8 0

4 years ago

5x^4x-2 what's result

pashok25 [27]

Answer:

There is no result.

Step-by-step explanation:

This question does not have an answer, as you would need to plug in an x value to get any sort of answer.

3 0

3 years ago

This is the question I don't understand​

This is the question I don't understand