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Ira Lisetskai [31]
3 years ago
14

What is the difference between an observational study and an experiment

Mathematics
1 answer:
Blizzard [7]3 years ago
4 0

Answer: In observational study observer has no control on the variables but in an experiment experimenter has control over the independent variable to record the change on the dependent variable.

Step-by-step explanation:

In statistics , an observational study is a study in which a researcher just observe effects on subjects in a certain manner without interfering them.

On the other hand an experiment is a process which is done by experimenter to  demonstrate a known fact or create a discovery by applying some methods to the variables  .

The basic difference between an observational study and an experiment is<em> in observational study observer has no control on the variables but in an experiment experimenter has control over the independent variable to record the change on the dependent variable.</em>

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Simplify each expression by writing the expression without absolute value bars
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Answer:

-1

Step-by-step explanation:

When b<4

|b-4|  is negative

|b-4|  = - ( b-4)

- (b-4) / ( b-4) =

Factoring out (b-4)

-1

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Multiply. Write your answer in scientific notation.<br> (8.8 x 10')(7.5 x 10<br> 10 )
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Illustrate it in standard form of quadratic equations.<br>1. 7x - 7 + 3x^2 = 0​
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Answer:

I love algebra anyways

The ans is in the picture with the  steps how i got it

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Step-by-step explanation:

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2 years ago
Assume that population mean is to be estimated from the sample described. Use the sample results to approximate the margin of er
Vikentia [17]

Answer:

ME=1.998 \frac{4}{\sqrt{64}}=0.999 \approx 1

Step-by-step explanation:

Previous concepts

A confidence interval is "a range of values that’s likely to include a population value with a certain degree of confidence. It is often expressed a % whereby a population means lies between an upper and lower interval".

The margin of error is the range of values below and above the sample statistic in a confidence interval.

Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".

\bar X =69 represent the sample mean for the sample  

\mu population mean

s=4.0 represent the sample standard deviation

n=64 represent the sample size  

Assuming the X follows a normal distribution

X \sim N(\mu, \sigma)

The sample mean \bar X have the following distribution:

\bar X \sim N(\mu, \frac{\sigma}{\sqrt{n}})

The margin of error for the sample mean is given by this formula:

ME=z_{\alpha/2}\frac{\sigma}{\sqrt{n}}

Since we have the sample standard deviation we can estimate the margin of error like this:

ME=t_{\alpha/2}\frac{s}{\sqrt{n}}

The next step would be find the value of \z_{\alpha/2}, \alpha=1-0.95=0.05 and \alpha/2=0.025

We can find the degrees of freedom like this:

df=n-1=64-1=63

And we can find the critical value with the following code in excel for example: "=T.INV(0.025,63)" and we got:

t_{\alpha/2}=\pm 1.998

And the margin of error would be :

ME=1.998 \frac{4}{\sqrt{64}}=0.999 \approx 1

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