You have 800 quarter-inch-long beads. if you use them all to make 16 bracelets, what will be the rate of beads per bracelet

Ms.Sack owns a grocerystore. She buys 272 pounds of potatoes for $99. She wants to sell them for twice as much. She makes 9 bags

mars1129 [50]

99*2=$198
10*9=90
272-90=182/5=36.5

4 0

2 years ago

Read 2 more answers

Lucas works for a salary of $2,396 per month. His deductions include $360 of federal income tax, $148 for Social Security, $35 f

lana [24]

Answer:

Lucas monthly net pay is $1758

Step-by-step explanation:

Lucas works for a salary of $2,396 per month.

His deductions include $360 of federal income tax,

$148 for Social Security,

$35 for Medicare, and

a $95 insurance premium.

Now,

2396 - 360 - 148 - 35 - 95 = 1758

Thus, Lucas monthly net pay is $1758

<u>-TheUnknownScientist</u>

7 0

3 years ago

Which operation should you perform first when you simplify the expression below? 10 ÷ 2 + 3(8 × 9)= A addition B subtraction C m

N76 [4]

C. multiplication (the 8 x 9 within the parenthesis)

8 0

3 years ago

Suppose 52% of the population has a college degree. If a random sample of size 563563 is selected, what is the probability that

amm1812

Answer:

The value is $P(| \^ p - p| < 0.05 ) = 0.9822$

Step-by-step explanation:

From the question we are told that

The population proportion is $p = 0.52$

The sample size is n = 563

Generally the population mean of the sampling distribution is mathematically represented as

$\mu_{x} = p = 0.52$

Generally the standard deviation of the sampling distribution is mathematically evaluated as

$\sigma = \sqrt{\frac{ p(1- p)}{n} }$

=> $\sigma = \sqrt{\frac{ 0.52 (1- 0.52 )}{563} }$

=> $\sigma = 0.02106$

Generally the probability that the proportion of persons with a college degree will differ from the population proportion by less than 5% is mathematically represented as

$P(| \^ p - p| < 0.05 ) = P( - (0.05 - 0.52 ) < \^ p < (0.05 + 0.52 ))$

Here $\^ p$ is the sample proportion of persons with a college degree.

So

$P( - (0.05 - 0.52 ) < \^ p < (0.05 + 0.52 )) = P(\frac{[[0.05 -0.52]]- 0.52}{0.02106} < \frac{[\^p - p] - p}{\sigma } < \frac{[[0.05 -0.52]] + 0.52}{0.02106} )$