At a large bank, account balances are normally distributed with a mean of $1,637.52 and a standard deviation of $623.16. What is the probability that a simple random sample of 400 accounts has a mean that exceeds $1,650?

Answers

Answer 1
Answer:

Answer:

P(\bar X >1650)=P(Z>(1650-1637.52)/((623.16)/(√(400)))=0.401)

And we can use the complement rule and we got:

P(Z>0.401) =1-P(Z<0.401) = 1-0.656= 0.344

Step-by-step explanation:

Previous concepts

Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".

The Z-score is "a numerical measurement used in statistics of a value's relationship to the mean (average) of a group of values, measured in terms of standard deviations from the mean".  

Solution to the problem

Let X the random variable that represent the bank account balances of a population, and for this case we know the distribution for X is given by:

X \sim N(1637.52,623.16)  

Where \mu=1637.52 and \sigma=623.16

Since the distribution of X is normal then the distribution for the sample mean \bar X is given by:

\bar X \sim N(\mu, (\sigma)/(√(n)))

And we can use the z score formula given by:

z = (\bar X -\mu)/((\sigma)/(√(n)))

And using this formula we got:

P(\bar X >1650)=P(Z>(1650-1637.52)/((623.16)/(√(400)))=0.401)

And we can use the complement rule and we got:

P(Z>0.401) =1-P(Z<0.401) = 1-0.656= 0.344

Answer 2
Answer:

Answer: the probability is 0.49

Step-by-step explanation:

Since the account balances at the large bank are normally distributed.

we would apply the formula for normal distribution which is expressed as

z = (x - µ)/σ

Where

x = account balances.

µ = mean account balance.

σ = standard deviation

From the information given,

µ = $1,637.52

σ = $623.16

We want to find the probability that a simple random sample of 400 accounts has a mean that exceeds $1,650. It is expressed as

P(x > 1650) = 1 - P(x ≤ 1650)

For x = 1650,

z = (1650 - 1637.52)/623.16 = 0.02

Looking at the normal distribution table, the probability corresponding to the z score is 0.51

P(x > 1650) = 1 - 0.51 = 0.49


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Really easy seventh grade math can I get this problem answered? Thanks!!

14V + 5 − 5V = 4(V + 15)

Answers

Answer:

V=11

Step-by-step explanation:

Simplify:

14V-5V+5=4V+60

9V+5=4V+60

Subtract 4V on both sides:

9V-4V+5=4V-4V+60

Solve:

5V+5=60

Subtract 5 on both sides:

5V+5-5=60-5

5V=55

Divide by 5

V=11

Hope this helps!

Step-by-step explanation:

14V+ 5 - 5V= 4V+ 60|-60|-4V

14V + 5 -5 V - 60 - 4V =0

<=> 5V - 55 =0 |+55

<=> 5V = 55 |:5

<=> V= 11

One basketball team played 30 games throughout their entire season. If this team won 80% of those games, how many games did they win? Enter a numerical answer only.

Answers

the team won 24 games out of 30

Equivalent expression for 18x-12x

Answers

Answer:

(18x - 12x) = (18 - 12)x = \boxed{6x}✓

Equivalent expression for (18x-12x) is 6x.

6x is the right answer.

6x will be your answer !!

Calculate the total number of pizzas that must be bought for a birthday party ifeach pizza is cut into 8 slices and each 26 children invited would be given 3
slices.

Answers

Answer:

10

Step-by-step explanation:

26×3=78

78÷8=9.75

round up to 10 since you can't buy .75 of a pizza

You buy a gym membership for $60 and then pay $40 each month. If you have atmost $210 to spend on the membership, how many months can you use the
gym?

Answers

Answer:3

Step-by-step explanation:

The mail arrival time to a department has a uniform distribution over 5 to 45 minutes. What is the probability that the mail arrival time is more than 25 minutes on a given day? Answer: (Round to 2 decimal places.)

Answers

Answer:

0.5

Step-by-step explanation:

An uniform probability is a case of probability in which each outcome is equally as likely.

For this situation, we have a lower limit of the distribution that we call a and an upper limit that we call b.

The probability that we find a value X higher than x is given by the following formula.

P(X > x) = (b - x)/(b-a)

The mail arrival time to a department has a uniform distribution over 5 to 45 minutes.

This means that a = 5, b = 45.

What is the probability that the mail arrival time is more than 25 minutes on a given day?

P(X > 25) = (45 - 25)/(45 - 5) = 0.5

So the probability that the mail arrival time is more than 25 minutes on a given day is 0.5.