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Len [333]
3 years ago
6

90 out of 120 students like pizza. what percent of students did not like pizza?

Mathematics
2 answers:
Pie3 years ago
5 0

Answer:

25%

Step-by-step explanation:

90/120=0.75

1-0.75=0.25

0.25x100= 25%

sergij07 [2.7K]3 years ago
5 0

Answer:

Hello There!!

Step-by-step explanation:

90/120=75/100 you divide 120 by 1.2 and do the same for the numerator.75% like pizza.100-75=25 so 25% don't like pizza.

hope this helps,have a great day!!

~Pinky~

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A new post-surgical treatment is being compared with a standard treatment. Seven subjects receive the new treatment, while seven
AnnyKZ [126]

Answer:

t=\frac{17.71-28.71}{\sqrt{\frac{4.461^2}{7}+\frac{7.387^2}{7}}}}=-3.372  

df=n_{S}+n_{N}-2=7+7-2=12

Since is a one sided test the p value would be:

p_v =P(t_{(12)}

If we compare the p value and the significance level given \alpha=0.05 we see that p_v so we can conclude that we have enough evidence to reject the null hypothesis, so we can conclude that the mean time for the new treatment is significantly lower than the time for the standard treatment at 5% of significance.

Step-by-step explanation:

New: 12, 13,15,19,20,21

Standard: 18,23,24,30,32,35

We can calculate the sample mean and deviation with the following formulas:

\bar X = \frac{\sum_{i=1}^n X_i}{n}

s= \sqrt{\frac{\sum_{i=1}^n (X_i -\bar X)^2}{n-1}}

Data given and notation

\bar X_{N}=17.71 represent the mean for the new case

\bar X_{S}=28.71 represent the mean for the standard case

s_{N}=4.461 represent the sample standard deviation for the new case

s_{S}=7.387 represent the sample standard deviation for the standard case

n_{S}=7 sample size selected for the standard case

n_{N}=7 sample size selected for the new case

\alpha=0.05 represent the significance level for the hypothesis test.

t would represent the statistic (variable of interest)

p_v represent the p value for the test (variable of interest)

State the null and alternative hypotheses.

We need to conduct a hypothesis in order to check if recovery time for patients who receive the new treatment is less than the mean for patients who receive the standard treatment, the system of hypothesis would be:

Null hypothesis:\mu_{N} \geq \mu_{S}

Alternative hypothesis:\mu_{N} < \mu_{S}

If we analyze the size for the samples both are less than 30 so for this case is better apply a t test to compare means, and the statistic is given by:

t=\frac{\bar X_{N}-\bar X_{S}}{\sqrt{\frac{s^2_{N}}{n_{N}}+\frac{s^2_{S}}{n_{S}}}} (1)

t-test: "Is used to compare group means. Is one of the most common tests and is used to determine whether the means of two groups are equal to each other".

Calculate the statistic

We can replace in formula (1) the info given like this:

t=\frac{17.71-28.71}{\sqrt{\frac{4.461^2}{7}+\frac{7.387^2}{7}}}}=-3.372  

P-value

The first step is calculate the degrees of freedom, on this case:

df=n_{S}+n_{N}-2=7+7-2=12

Since is a one sided test the p value would be:

p_v =P(t_{(12)}

Conclusion

If we compare the p value and the significance level given \alpha=0.05 we see that p_v so we can conclude that we have enough evidence to reject the null hypothesis, so we can conclude that the mean time for the new treatment is significantly lower than the time for the standard treatment at 5% of significance.

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Answer:

Allison

Step-by-step explanation:

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Answer:

Y=3x+16

Step-by-step explanation:

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