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enot [183]
3 years ago
15

Solve for brainliest please

Mathematics
2 answers:
Romashka-Z-Leto [24]3 years ago
7 0

Answer : D=19

◊ YusuCr ◊

velikii [3]3 years ago
4 0

Answer: The value of d 62 + 5

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Matthew had exactly 20 pennies in his pocket. Five were Canadian pennies and the rest were U.S. Pennies. If he took 1 penny out
Lemur [1.5K]

Answer:

1/4

This is also same as 0.25

Step-by-step explanation:

Probability is the ratio of the number of possible outcomes to the total outcome.

Given that there are 20 pennies and 5 were Canadian pennies, this means that the number of American  pennies

= 20 - 5

= 15

If one penny is taken out of his pocket at random, the probability or odds that it would be a Canadian penny P(C)

= 5/20

= 1/4 (To the lowest term)

= 0.25 ( in decimal)

7 0
3 years ago
The following questions pertain to the properties of the STANDARD NORMAL distribution. (a) True or False: The distribution is be
SashulF [63]

Answer:

a. The distribution is bell-shaped and symmetric: True.

b. The distribution is bell-shaped and symmetric: True.

c. The probability to the left of the mean is 0: False.

d. The standard deviation of the distribution is 1: True.

Step-by-step explanation:

The Standard Normal distribution is a normal distribution with <em>mean</em>, \\ \mu = 0, and <em>standard deviation</em>, \\ \sigma = 1.

It is important to recall that the parameters of the Normal distributions, namely, \\ \mu and \\ \sigma characterized them.

We can use the Standard Normal distribution to find probabilities for any normally distributed data. All we have to do is normalized them through z-scores:

\\ z = \frac{x - \mu}{\sigma} [1]

Where \\ x is the raw score that we want to standardize.

Therefore, taking into account all this information, we can answer the following questions about the Standard Normal distribution:

(a) True or False: The distribution is bell-shaped and symmetric

Answer: True. As the normal distribution, the standard normal distribution is also bell-shape and it is symmetrical around the mean. The standardized values or <em>z-scores</em>, which represent the <em>distance from the mean in standard deviations units</em>, are the same but when it is <em>above</em> the mean, the z-score is <em>positive</em>, and <em>negative</em> when it is <em>below</em> the mean. This result is a <em>consequence of the symmetry</em> of this distribution respect to the mean of the distribution.

(b) True or False: The mean of the distribution is 0.

Answer: True. Since the Standard Normal uses standardized values, if we use [1], we have:

\\ z = \frac{x - \mu}{\sigma}

If \\ x = \mu

\\ z = \frac{\mu - \mu}{\sigma}

\\ z = \frac{0}{\sigma}

\\ z = 0

Then, the value for the mean is where z = 0. A z-score is a linear transformation of the original data. For this reason, the transformed mean is equivalent to 0 in the standard normal distribution. We only need to find distances from this zero in standard normal deviations or z-scores to find probabilities.

(c) True or False: The probability to the left of the mean is 0.

Answer: False. The probability to the left of the mean is not 0. The cumulative probability from \\ -\infty until the mean is 0.5000 or \\ P(-\infty < z < 0) = 0.5.

(d) True or False: The standard deviation of the distribution is 1.

Answer: True. The standard normal distribution is a convenient way of calculate probabilities for any normal distribution. The standardized variable, represented by [1], permits us to use one table (the standard normal table) for all normal distributions.

In this distribution, the <em>z-score is always divided by the standard deviation of the population. </em>Then<em>, </em>the standard deviation for the <em>standard normal distribution</em> are times or fractions of the standard deviation of the population, since we divide the distance of a raw score from the mean of the population, \\ x - \mu, by it. As a result, the standard deviation for the standard normal distribution will be times (1, 2, 3, 0.96, -1, -2, etc) the standard deviation of any normal distribution, \\ \sigma.

In this case, the linear transformation of the original data for one standard deviation from the mean is z = 1. Therefore, the standard deviation for the standard normal distribution is the unit.

6 0
3 years ago
Read 2 more answers
What is the value of (X) for this equation 3(8x+3) − 263 = −6x+7
olganol [36]

Answer: 87/10

Step-by-step explanation:

7 0
4 years ago
The summit of mt. whitney in california is 14494 ft above sea level. what is that height in yards?
Umnica [9.8K]
Hey there,
14494 feet = 4831.3333 yards 
                 = 4831.3 yards

Hope this helps :))

~Top
7 0
4 years ago
Read 2 more answers
What is 304967000 and word form
Rainbow [258]
<span>Three hundred four million nine hundred sixty-seven thousand.</span>
6 0
3 years ago
Read 2 more answers
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