Convert 386 milligrams to grams. 0.386 g 3.86 g 38.6 g 3,860 g

Now to do this, we need to get the amount of profit she made. That's quite easy, we only need to subtract the cost price from the selling price. And that equals $15 - $9.38 that equals $5.62.

Now, we divide this value by the cost price and multiply by 100% to get the percentage gain.

I.e 5.62/9.38 × 100%.

That gives 59.9% , which equals 60% when approximated to the nearest percentage.

5 0

3 years ago

Write an inequality that represents the real-world problem. then select all that apply

Alekssandra [29.7K]

Answer:

where is the problem

Step-by-step explanation:

6 0

3 years ago

National data indicates that 35% of households own a desktop computer. In a random sample of 570 households, 40% owned a deskt

Elan Coil [88]

Answer:

Yes, this provide enough evidence to show a difference in the proportion of households that own a desktop.

Step-by-step explanation:

We are given that National data indicates that 35% of households own a desktop computer.

In a random sample of 570 households, 40% owned a desktop computer.

Let p = population proportion of households who own a desktop computer

SO, Null Hypothesis, $H_0$ : p = 25% {means that 35% of households own a desktop computer}

Alternate Hypothesis, $H_A$ : p $\neq$ 25% {means that % of households who own a desktop computer is different from 35%}

The test statistics that will be used here is One-sample z proportion statistics;

T.S. = $\frac{\hat p-p}{{\sqrt{\frac{\hat p(1-\hat p)}{n} } } } }$ ~ N(0,1)

where, $\hat p$ = sample proportion of 570 households who owned a desktop computer = 40%

n = sample of households = 570

So, test statistics = $\frac{0.40-0.35}{{\sqrt{\frac{0.40(1-0.40)}{570} } } } }$

= 2.437

Since, in the question we are not given with the level of significance at which to test out hypothesis so we assume it to be 5%. Now at 5% significance level, the z table gives critical values of -1.96 and 1.96 for two-tailed test. Since our test statistics doesn't lies within the range of critical values of z so we have sufficient evidence to reject our null hypothesis as it will fall in the rejection region due to which we reject our null hypothesis.

Therefore, we conclude that % of households who own a desktop computer is different from 35%.

3 0

3 years ago