What is the decimal equal to 1/6
2 answers:
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Answer:
The picture is 4.25 inches from the side of the paper
Step-by-step explanation:
- Taylor wants to center a 3.5 inch picture on a piece of paper that is
12 inches wide
- Lets think about that he want to put the picture in the center of the
paper, then divide the length of the paper into two equal parts and the
picture into two equal part
∵ The width of the paper is 12 inches
∵ 12 ÷ 2 = 6 inches
∵ The width of the picture is 3.5 inches
∵ 3.5 ÷ 2 = 1.75
- Now lets subtract from 6 inches (half paper) 1.75 inches (half picture)
to find the distance between the side of the paper and the picture
∵ 6 - 1.75 = 4.25
∴ The distance from the side of the paper to the picture is 4.25 inches
* <em>The picture is 4.25 inches from the side of the paper</em>
* Look to attached figure for more understand
Given:
μ = 25 mpg, the population mean
σ = 2 mpg, the population standard deviation
If we select n samples for evaluation, we should calculate z-scores that are based on the standard error of the mean.
That is,
The random variable is x = 24 mpg.
Part (i): n = 1
σ/√n = 2
z = (24 -25)/2 = -0.5
From standard tables,
P(x < 24) = 0.3085
Part (ii): n = 4
σ/√n = 1
z = (24 -25)/1 = -1
P(x < 24) = 0.1587
Part (iii): n=16
σ/√n = 0.5
z = (24 - 25)/0.5 = -2
P(x < 24) = 0.0228
Explanation:
The larger the sample size, the smaller the standard deviation.
Therefore when n increases, we are getting a result which is closer to that of the true mean.
μ = 25 mpg, the population mean
σ = 2 mpg, the population standard deviation
If we select n samples for evaluation, we should calculate z-scores that are based on the standard error of the mean.
That is,
The random variable is x = 24 mpg.
Part (i): n = 1
σ/√n = 2
z = (24 -25)/2 = -0.5
From standard tables,
P(x < 24) = 0.3085
Part (ii): n = 4
σ/√n = 1
z = (24 -25)/1 = -1
P(x < 24) = 0.1587
Part (iii): n=16
σ/√n = 0.5
z = (24 - 25)/0.5 = -2
P(x < 24) = 0.0228
Explanation:
The larger the sample size, the smaller the standard deviation.
Therefore when n increases, we are getting a result which is closer to that of the true mean.