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ycow [4]
3 years ago
14

You make $25000 a year, and you get a 10% raise. Your new salary is $____ The next year you get a 10% cut. Your new salary is $_

____. That is ____% less than your initial salary.
Mathematics
1 answer:
gtnhenbr [62]3 years ago
6 0

Firstly, we have to find out what 10% of $25000 is. To do this, multiply $25000 by 0.1 (10% in decimal form): \$25000 \times 0.1=\$2500 . <em>$2500 is the 10% raise.</em>

Next, to find your first new salary, add $25000 and $2500 together: \$25000+\$2500=\$27500 . <u>$27500 is your new salary after the 10% raise.</u>

Next, we need to find 10% of $27500. It's a similar process as to finding 10% of $25000. \$27500 \times 0.1=\$2750 . <em>$2750 is your 10% cut.</em>

Next, since this is a cut, subtract $2750 from $27500. \$27500-\$2750=\$24750 . <u>$24750 is your new salary after the 10% cut.</u>

Next, to find the percentage change, firstly divide $24750 by $25000. \frac{\$24750}{\$25000}=0.99\ \textsf{or}\ 99\% . Now this shows that your current salary is 99% of what you used to make. It is <em>not</em> how much less you make. To find how much less it is, subtract 99% from 100%: 100\%-99\%=1\% . <u>Your current salary is 1% less than what you used to make.</u>

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\mu_p -\sigma_p = 0.74-0.0219=0.718

\mu_p +\sigma_p = 0.74+0.0219=0.762

68% of the rates are expected to be betwen 0.718 and 0.762

\mu_p -2*\sigma_p = 0.74-2*0.0219=0.696

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Step-by-step explanation:

Check for conditions

For this case in order to use the normal distribution for this case or the 68-95-99.7% rule we need to satisfy 3 conditions:

a) Independence : we assume that the random sample of 400 students each student is independent from the other.

b) 10% condition: We assume that the sample size on this case 400 is less than 10% of the real population size.

c) np= 400*0.74= 296>10

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So then we have all the conditions satisfied.

Solution to the problem

For this case we know that the distribution for the population proportion is given by:

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\sigma_p =\sqrt{\frac{0.74(1-0.74)}{400}}=0.0219

The empirical rule, also referred to as the three-sigma rule or 68-95-99.7 rule, is a statistical rule which states that for a normal distribution, almost all data falls within three standard deviations (denoted by σ) of the mean (denoted by µ). Broken down, the empirical rule shows that 68% falls within the first standard deviation (µ ± σ), 95% within the first two standard deviations (µ ± 2σ), and 99.7% within the first three standard deviations (µ ± 3σ).

\mu_p -\sigma_p = 0.74-0.0219=0.718

\mu_p +\sigma_p = 0.74+0.0219=0.762

68% of the rates are expected to be betwen 0.718 and 0.762

\mu_p -2*\sigma_p = 0.74-2*0.0219=0.696

\mu_p +2*\sigma_p = 0.74+2*0.0219=0.784

95% of the rates are expected to be betwen 0.696 and 0.784

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\mu_p +3*\sigma_p = 0.74+3*0.0219=0.806

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