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mel-nik [20]
1 year ago
14

I have 90% after about 75%

Mathematics
1 answer:
kkurt [141]1 year ago
6 0

The lowest grade he could earn is 120% of the grade at the end of the semester.

The following statement is given:

I have 90% after about 75% of the semester.

We are asked to find the lowest grade by the end of this semester.

<h3>What is Percentage?</h3>

A percentage is a number expressed as a fraction of 100.

- 50% = 50/100 = 1/2

- 25% = 25/100 = 1/4

- 20% = 20/100 = 1/5.

We can write this statement "I have a 90% grade after about 75% of the semester" as:

90% grade  =  75% semester.............(1)


By the end of the semester means at 100% semester.

Multiplying equation (1) by 100/ 75 on both sides of the equation.

We get,

(100/75) x 90% grade = (100/75) x 75% semester

(100 x 90)/75 % grade = 100% semester

120% grade = 100%

Thus the lowest grade he could earn is 120% of the grade at the end of the semester.

Learn more about Percentages here:

brainly.com/question/24159063

#SPJ1

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Using the z-distribution, as we have a proportion, the 95% confidence interval is (0.2316, 0.3112).

<h3>What is a confidence interval of proportions?</h3>

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In which:

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  • z is the critical value.
  • n is the sample size.

In this problem, we have a 95% confidence level, hence\alpha = 0.95, z is the value of Z that has a p-value of \frac{1+0.95}{2} = 0.975, so the critical value is z = 1.96.

We also consider that 130 out of the 479 season ticket holders spent $1000 or more at the previous two home football games, hence:

n = 479, \pi = \frac{130}{479} = 0.2714

Hence the bounds of the interval are found as follows:

\pi - z\sqrt{\frac{\pi(1-\pi)}{n}} = 0.2714 - 1.96\sqrt{\frac{0.2714(0.7286)}{479}} = 0.2316

\pi + z\sqrt{\frac{\pi(1-\pi)}{n}} = 0.2714 + 1.96\sqrt{\frac{0.2714(0.7286)}{479}} = 0.3112

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Consider the following hypothesis test.H0:μ1−μ2=0 Ha:μ1−μ2≠0The following results are for two independent samples taken from the
Julli [10]

Answer:

a) z =\frac{104-106}{\sqrt{\frac{8.4^2}{80} +\frac{7.6^2}{70}}}= -1.53  

b) p_v =2*P(z

c) Since the p value is higher than the significance level provided we have enogh evidence to FAIL to reject the null hypothesis and we can't conclude that the true means are different at 5% of significance

Step-by-step explanation:

Information given

\bar X_{1}= 104 represent the mean for 1

\bar X_{2}= 106 represent the mean for 2

\sigma_{1}= 8.4 represent the population standard deviation for 1

\sigma_{2}= 7.6 represent the population standard deviation for 2

n_{1}=80 sample size for the group 1

n_{2}=70 sample size for the group 2

z would represent the statistic

Hypothesis to test

We want to check if the two means for this case are equal or not, the system of hypothesis would be:

H0:\mu_{1}=\mu_{2}

H1:\mu_{1} \neq \mu_{2}

The statistic would be given by:

z =\frac{\bar X_1-\bar X_2}{\sqrt{\frac{\sigma^2_1^2}{n_1} +\frac{\sigma^2_2^2}{n_2}}}=(1)

Part a

Replacing we got:

z =\frac{104-106}{\sqrt{\frac{8.4^2}{80} +\frac{7.6^2}{70}}}= -1.53

Part b

The p value would be given by this probability:

p_v =2*P(z

Part c

Since the p value is higher than the significance level provided we have enogh evidence to FAIL to reject the null hypothesis and we can't conclude that the true means are different at 5% of significance

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