Please answer all :3

Mathematics

1 answer:

My name is Ann [436]3 years ago

5 0

Answer:

1 - First question = 6.00 | Second Question = 0.06

2 - Didnt know

3 - 1360, from 1.36kg

4 - 0.3175

5 - 20.5

6 - 18

7 - 965606.4

Step-by-step explanation:

sorry I couldn't give you number 2, but here are the rest of the answers

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HELP PLEASE I NEED TO KNOW --> SUPER EASY QUESTION

aev [14]

Answer:

As functions of a true variable, exponential functions are uniquely characterized by the very fact that the expansion rate of such a function (that is, its derivative) is directly proportional to the value of the function.

Step-by-step explanation:

Have a nice day hope this helps.

5 0

2 years ago

The National Center for Education Statistics surveyed a random sample of 4400 college graduates about the lengths of time requir

Paha777 [63]

Answer:

95% confidence interval for the mean time required to earn a bachelor’s degree by all college students is [5.10 years , 5.20 years].

Step-by-step explanation:

We are given that the National Center for Education Statistics surveyed a random sample of 4400 college graduates about the lengths of time required to earn their bachelor’s degrees. The mean was 5.15 years and the standard deviation was 1.68 years respectively.

Firstly, the pivotal quantity for 95% confidence interval for the population mean is given by;

P.Q. = $\frac{\bar X-\mu}{\frac{\sigma}{\sqrt{n} } }$ ~ N(0,1)

where, $\bar X$ = sample mean time = 5.15 years

$\sigma$ = sample standard deviation = 1.68 years

n = sample of college graduates = 4400

$\mu$ = population mean time

Here for constructing 95% confidence interval we have used One-sample z test statistics although we are given sample standard deviation because the sample size is very large so at large sample values t distribution also follows normal.

So, 95% confidence interval for the population mean, $\mu$ is ;

P(-1.96 < N(0,1) < 1.96) = 0.95 {As the critical value of z at 2.5%

level of significance are -1.96 & 1.96}

P(-1.96 < $\frac{\bar X-\mu}{\frac{\sigma}{\sqrt{n} } }$ < 1.96) = 0.95

P( $-1.96 \times {\frac{\sigma}{\sqrt{n} } }$ < ${\bar X-\mu}$ < $1.96 \times {\frac{\sigma}{\sqrt{n} } }$ ) = 0.95