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Gnom [1K]
2 years ago
14

Can someone who isn’t a bot answer this for me. If I see a link or file I’ll delete this god forsaken app.

Mathematics
2 answers:
lara31 [8.8K]2 years ago
4 0

Answer: √62 goes down the path √62 and 45° goes down path up

Step-by-step explanation:

IRINA_888 [86]2 years ago
4 0

Answer:

2√31

Step-by-step explanation:

Here,

The type of triangle is right angled triangle.

Given,

θ = 45

Hypotenuse = x

Opposite side = √62

To find : x = ?

Formula : -

sin θ = Opposite side / Hypotenuse.

Note : -

The value of sin 45 = 1 / √2

sin 45 = √62 / x

1 / √2 = √62 / x

x = √62 * √2

( √62 = √31 * √2 )

x = √62 * √2

= √31 * √2 * √2

= √31 * 2

x = 2√31

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The results of a common standardized test used in psychology research is designed so that the population mean is 155 and the sta
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Answer:

The value <em>155</em> is zero standard deviations from the [population] mean, because \\ x = \mu, and therefore \\ z = 0.

Step-by-step explanation:

The key concept we need to manage here is the z-scores (or standardized values), and we can obtain a z-score using the next formula:

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

Where

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  • \\ \sigma is the <em>population standard deviation</em>.

Carefully looking at [1], we can interpret it as <em>the distance from the mean of a raw value in standard deviations units. </em>When the z-score is <em>negative </em>indicates that the raw score, <em>x</em>, is <em>below</em> the population mean, \\ \mu. Conversely, a <em>positive</em> z-score is telling us that <em>x</em> is <em>above</em> the population mean. A z-score is also fundamental when determining probabilities using the <em>standard normal distribution</em>.

For example, think about a z-score = 1. In this case, the raw score is, after being standardized using [1], <em>one standard deviation above</em> from the population mean. A z-score = -1 is also one standard deviation from the mean but <em>below</em> it.

These standardized values have always the same probability in the <em>standard normal distribution</em>, and this is the advantage of using it for calculating probabilities for normally distributed data.

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From the question, we know that:

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Having into account all the previous information, we can say that the raw score, <em>x = 155</em>, is <u><em>zero standard deviations units from the mean.</em></u> <u><em>The subject   earned a score that equals the population mean.</em></u> Then, using [1]:

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

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\\ z = \frac{0}{50}

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As we say before, the z-score "tells us" the distance from the population mean, and in this case this value equals zero:  

\\ x = \mu

Therefore

\\ z = 0

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