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Mandarinka [93]
3 years ago
8

Do humans beings live for as long as a million hours? Explain reasoning and calculations.

Mathematics
1 answer:
Dima020 [189]3 years ago
8 0

My first reaction is to say: "In that case, you ought to get busy."

(1,000,000 hours) x (1 day / 24 hours) x (1 year / 365.25 days) =

     (1,000,000 x 1 x 1) / (24 x 365.25)    years =

                             114.08 years .

A few human beings live that long.
Most don't.

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Step-by-step explanation: hope this help

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The following data comparing wait times at two rides at Disney are listed below: Position Pirates Splash Mountain Sample Size 32
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Answer:

a) (14.68 -18.77) - 2.39 \sqrt{\frac{11.87^2}{32}+\frac{16.79^2}{30}} =-12.968

(14.68 -18.77) + 2.39 \sqrt{\frac{11.87^2}{32}+\frac{16.79^2}{30}} =4.788

b) t=\frac{14.68-18.77}{\sqrt{\frac{11.87^2}{32}+\frac{16.79^2}{30}}}}=-1.10  

Step-by-step explanation:

Data given and notation

\bar X_{A}=14.68 represent the mean for Pirates

\bar X_{B}=18.77 represent the mean for Splash Mountain

s_{A}=11.87 represent the sample standard deviation for the sample Pirates

s_{B}=16.79 represent the sample standard deviation for the sample Slpash Mountain

n_{A}=32 sample size selected for Pirates

n_{B}=30 sample size selected for Splash Mountain

\alpha=0.02 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)

Part a

The confidence interval would be given by:

(\bar X_A -\bar X_B) \pm t_{\alpha/2} \sqrt{\frac{s^2_{A}}{n_{A}}+\frac{s^2_{B}}{n_{B}}}

The degrees of freedom are given by:

df = n_A +n_B -2 = 32+30-2 = 60

Since we want 98% of confidence the significance level is \alpha =1-0.98 =0.02 and \alpha/2 =0.01, we can find in the t distribution with df =60 a critical value that accumulates 0.01 of the area on each tail and we got:

t_{\alpha/2}= 2.39

And replacing we got for the confidence interval:

(14.68 -18.77) - 2.39 \sqrt{\frac{11.87^2}{32}+\frac{16.79^2}{30}} =-12.968

(14.68 -18.77) + 2.39 \sqrt{\frac{11.87^2}{32}+\frac{16.79^2}{30}} =4.788

Part b

State the null and alternative hypotheses.

We need to conduct a hypothesis in order to check if the means are equal, the system of hypothesis would be:

Null hypothesis:\mu_{A} = \mu_{B}

Alternative hypothesis:\mu_{A} \neq \mu_{B}

the statistic is given by:

t=\frac{\bar X_{A}-\bar X_{B}}{\sqrt{\frac{s^2_{A}}{n_{A}}+\frac{s^2_{B}}{n_{B}}}} (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{14.68-18.77}{\sqrt{\frac{11.87^2}{32}+\frac{16.79^2}{30}}}}=-1.10  

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