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Mnenie [13.5K]
3 years ago
5

I cant understand algebra please help we will need to conversat​

Mathematics
1 answer:
Anarel [89]3 years ago
7 0

Answer:

here the value of x is 0.25

or

1/4

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(a) A survey of the adults in a town shows that 8% have liver problems. Of these, it is also found that 25% are heavy drinkers,
grandymaker [24]

Answer:

i. Has a liver problems?

= 0.08

ii. Is a heavy drinker ?

= 0.066

iii. If a person is found to be a heavy drinker, what is the probability that this person has liver problem?

= 0.303

iv. If a person is found to have liver problems, what is the probability that this person is a heavy drinker?

= 0.25

v. If a person is found to be a non –drinker, what is the probability that this person has liver problems?

= 0.104

Step-by-step explanation:

We have 2 Events in this question

Event A: People with liver problems

Event B : People without liver problems

Event A: People with liver problems

Let us represent people with liver problems as = (L)

a)8% have liver problems. = P(L)

Under liver problems we have:

b) 25% are heavy drinkers = P( L & H)

c) 35% are social drinkers = P( L & S)

d) 40% are non-drinkers. = P( L & N)

Event B( no liver problem)

Let us represent no liver problem as NL

We are not given in the question but Probability of having no liver problem = 100 - Probability of having liver problem

= 100 - 8% = 92 %

P(NL ) = 92%

From the question, For people without liver problems, we have:

a) 5% are heavy drinkers = P(NL & H)

b) 65% are social drinkers = P( NL & S)

c) 30% do not drink at all = P( NL & N)

An adult is chosen at random, what is the probability that this person

i. Has a liver problems?

P(L) = 8% or 0.08

ii. Is a heavy drinker ?

From the question, we have:

Probability of people that have liver problems and are heavy drinkers P(L & H) = 25% = 0.25

Probability of people that have do not have liver problems and are heavy drinkers P(NL & H) = 5% = 0.05

Probability ( Heavy drinker) =

P(L) × P(L & H) + P(NL) × P(NL & H)

= 0.25 × 0.08 + 0.05 × 0.92

= 0.066

iii. If a person is found to be a heavy drinker, what is the probability that this person has liver problem?

Probability (Heavy drinker and has liver problem) = [P(L) × P(L & H)] ÷ [P(L) × P(L & H)] + [P(NL) × P(NL & H) ]

= [0.25 × 0.08] ÷ [0.25 × 0.08] + [0.05 × 0.92]

= 0.303030303

Approximately = 0.303

iv. If a person is found to have liver problems, what is the probability that this person is a heavy drinker?

P(L & H) = 25% = 0.25

v. If a person is found to be a non –drinker, what is the probability that this person has liver problems.?

People with liver problems are non-drinkers. = P( L & N) = 40% = 0.4

People without liver problems and do not drink at all = P( NL & N) = 30% = 0.3

Probability (non drinker and has liver problem) = [P( L & N) × P(L & H)] ÷ [P( L & N) × P(L & H)] + [ P( NL & N) × P(NL & H) ]

= [0.4× 0.08] ÷ [0.4 × 0.08] + [0.3 × 0.92]

= 0.1038961039

Approximately ≈ 0.104

5 0
3 years ago
Over the past several years, the proportion of one-person households has been increasing. The Census Bureau would like to test t
bixtya [17]

Answer:

For this case we can find the critical value with the significance level \alpha=0.05 and if we find in the right tail of the z distribution we got:

z_{\alpha}= 1.64

The statistic is given by:

z=\frac{\hat p -p_o}{\sqrt{\frac{p_o (1-p_o)}{n}}} (1)  

Replacing we got:  

z=\frac{0.344 -0.27}{\sqrt{\frac{0.27(1-0.27)}{125}}}=1.86  

Since the calculated value is higher than the critical value we have enough evidence to reject the null hypothesis and we can conclude that the true proportion of households with one person is significantly higher than 0.27

Step-by-step explanation:

We have the following dataset given:

X= 43 represent the households consisted of one person

n= 125 represent the sample size

\hat p= \frac{43}{125}= 0.344 estimated proportion of  households consisted of one person

We want to test the following hypothesis:

Null hypothesis: p \leq 0.27

Alternative hypothesis: p>0.27

And for this case we can find the critical value with the significance level \alpha=0.05 and if we find in the right tail of the z distribution we got:

z_{\alpha}= 1.64

The statistic is given by:

z=\frac{\hat p -p_o}{\sqrt{\frac{p_o (1-p_o)}{n}}} (1)  

Replacing we got:  

z=\frac{0.344 -0.27}{\sqrt{\frac{0.27(1-0.27)}{125}}}=1.86  

Since the calculated value is higher than the critical value we have enough evidence to reject the null hypothesis and we can conclude that the true proportion of households with one person is significantly higher than 0.27

5 0
3 years ago
Elizabeth's credit card computes her finance charges using the previous balance method and a 30 day billing cycle. The table bel
Ostrovityanka [42]

Answer:

it has to be 21 because if calculate the bill cycle that what you get

7 0
3 years ago
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10,000+2,000+50+5 in standard form
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12,055 is the standard form
4 0
3 years ago
Read 2 more answers
Solve and<br> graph this<br> inequality.<br> -3x&gt;15
lara31 [8.8K]

Answer:

x > -5

Step-by-step explanation:

-3x > 15

divide by -3

x > -5

8 0
3 years ago
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