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givi [52]
3 years ago
11

According to Gallup’s annual poll on personal finances, while most U.S. workers reported living comfortably now, many expected a

downturn in their lifestyle when they stop working. Approximately 55% said they have enough money to live comfortably now and expected to do so in the future. If you select a sample of 200 U.S. workers, the probability is 90% that less than what sample percentage will say they expect to live comfortably? Answer with the percentage in decimal form to 4 decimal places.
Mathematics
1 answer:
tester [92]3 years ago
7 0

Answer:

- The required percentage to 4 d.p. = 59.5126%

- The required percentage in decimal point to 4 d.p. = 0.5951

Step-by-step explanation:

Proportion that said they have enough money to live comfortably now and expected to do so in the future = 55% = 0.55

Sample size = n = 200

The Central Limit Theorem ensures that we can say that:

1) The sample proportion is equal to the population proportion.

p = μₓ = μ = 0.55

2) Standard Deviation of the sampling distribution = σₓ = √[p(1-p)/n] = √(0.55×0.45/200) = 0.0352

3) We can say that the sample distribution approximates a normal distribution especially when

np > 5 and nq > 5 (which is true for this sample size)

The probability is 90% that less than what sample percentage will say they expect to live comfortably

To find this sample percentage, let that that sample percentage be x' and its z-score be z'

z' = (x' - μ)/σₓ

But we are told that

P(z < z') = 90% = 0.90

Using the normal distribution table

z' = 1.282

1.282 = (x' - 0.55)/0.0352

x' = 0.55 + (0.0352×1.282) = 0.5951264

Hence, the required sample percentage = 59.5126% to 4 d.p.

Hope this Helps!!!

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It is claimed that automobiles are driven on average more than 20,000 kilometers per year. To test this claim, 100 randomly sele
kow [346]

Answer:

t=\frac{23500-20000}{\frac{3900}{\sqrt{100}}}=8.974      

p_v =P(t_{99}>8.974)=9.43x10^{-15}  

If we compare the p value and the significance level given for example \alpha=0.05 we see that p_v so we can conclude that we to reject the null hypothesis, and the actual mean is significantly higher than 20000.      

Step-by-step explanation:

1) Data given and notation      

\bar X=23500 represent the sample mean  

s=3900 represent the sample standard deviation      

n=100 sample size      

\mu_o =2000 represent the value that we want to test    

\alpha 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 determine if the true mean is higher than 20000, the system of hypothesis would be:      

Null hypothesis:\mu \leq 2000      

Alternative hypothesis:\mu > 2000      

We don't know the population deviation, so for this case is better apply a t test to compare the actual mean to the reference value, and the statistic is given by:      

t=\frac{\bar X-\mu_o}{\frac{s}{\sqrt{n}}} (1)      

t-test: "Is used to compare group means. Is one of the most common tests and is used to determine if the mean is (higher, less or not equal) to an specified value".  

Calculate the statistic      

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

t=\frac{23500-20000}{\frac{3900}{\sqrt{100}}}=8.974      

Calculate the P-value      

First we need to calculate the degrees of freedom given by:  

df=n-1=100-1=99  

Since is a one-side upper test the p value would be:      

p_v =P(t_{99}>8.974)=9.43x10^{-15}  

Conclusion      

If we compare the p value and the significance level given for example \alpha=0.05 we see that p_v so we can conclude that we to reject the null hypothesis, and the actual mean is significantly higher than 20000.      

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Answer:

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So one value for x is 21+sqrt(253)

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Problem:

Given (21,7) and (x,1), find all x such that the distance between these two points is 17.

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