Finding SD by only knowing the mean and one other piece of information

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"The weights of bags of vegetables are approximately normally distributed with mean of 1kg. One quarter have weight greater than 1.1kg. Find the standard deviation."

I know this question might be simple to most of you, but probability/statistics really isn't my strong suit. I usually understand the standard deviation to be $\sigma=\sqrt{\sum(x_i-\mu)^2\cdot N^{-1}}$. In this case we aren't concerned with specific values of $x$ I don't think, and we don't know the sample size. All I can extrapolate from the question is that since it's 25% that have weight greater than 1.1kg then that 25% starts less than one standard deviation away from the mean.

If I were to guess, I would say that since this is normally distributed then I know that 34% of the bags fall within one standard deviation above the mean, and if 25% have a weight greater than 1.1kg, then 25% have a weight between 1kg and 1.1kg. So the deviation for 25% is 0.1kg which is less than 1 standard deviation, so I think I should multiply 0.1 by $\frac{34}{25}$ to get $0.136$ which, if my assumptions are correct, is equal to one standard deviation?

This doesn't feel concrete, I'm sure there's a more rigorous way to find the answer, any help is appreciated.

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All I can extrapolate from the question is that since it's 25% that have weight greater than 1.1kg

That´s true. So the equation $P(X\geq 1.1)=0.25$, where $X\sim \mathcal N(1, \sigma^2)$ Next we can standardize the random variable: $Z=\frac{X-\mu}{\sigma}$

So the equation is $P\left(Z\geq \frac{X-\mu}{\sigma}= \frac{1.1-1}{\sigma}\right)=0.25$. Thus

$$1-\Phi\left(\frac{0.1}{\sigma} \right)=0.25$$ Can you proceed?

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One quarter have weight greater than 1.1kg

I translate it for you: $75\%$ of bags has a weight that is less or equal to $1.1$ kg. Assuming normality with mean 1 this can be formalized in the following way

$$\Phi\Bigg(\frac{1.1-1}{\sigma}\Bigg)=0.75$$

$$\frac{1.1-1}{\sigma}\approx 0.6745$$

$$\sigma\approx 0.1483$$

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Given that the normal distribution is symmetric and that 1/4 of the vegetables have weight larger than 1.1 you can say:

$\int_{-\infty}^{0.9} f(x)· \,dx = 1/4 $

$\int_{0.9}^{1} f(x)· \,dx = 1/4 $

$\int_{1}^{1.1} f(x)· \,dx = 1/4 $

$\int_{1.1}^{+\infty} f(x)· \,dx = 1/4 $

The inter-quantile range (IQR) is defined as:

$IQR = Q_{75} - Q_{25} = 1.1 - 0.9 = 0.2$

It can be shown that for a normal distribution:

$IQR = 2 ·\phi^{-1}(0.75)·\sigma$

Where $\phi^{-1}$ is the inverse cumulative density function or quantile function of the standard normal distribution. Hence:

$\sigma = \frac{IQR}{2 ·\phi^{-1}(0.75)} \approx \frac{0.2}{2 · 0.6745} = 0.1483 $

To check the answer, you can ran in R:

x = rnorm(10000000, 1, 0.2/(2*qnorm(0.75)))
plot(density(x))
quantile(x)
# 0%       25%       50%       75%      100% 
# 0.2135559 0.9000991 1.0001097 1.0999769 1.7831438