Step 1 :First, we need to check if the given table represents a probability distribution. A probability distribution must satisfy two conditions: (1) all probabilities must be between 0 and 1 inclusive, and (2) the sum of all probabilities must equal 1.
Step 2 :Looking at the table, we can see that all probabilities are between 0 and 1 inclusive, so the first condition is satisfied.
Step 3 :To check the second condition, we sum up all the probabilities: $0.352 + 0.432 + 0.188 + 0.028 = 1$. So, the second condition is also satisfied.
Step 4 :Therefore, the table does represent a probability distribution.
Step 5 :Next, we need to find the mean of the random variable $x$. The mean, or expected value, of a discrete random variable is given by the sum of the product of each outcome and its probability. In mathematical terms, if $x$ is a random variable and $P(x)$ is the probability of $x$, then the mean $\mu$ is given by $\mu = \sum xP(x)$.
Step 6 :Substituting the given values into the formula, we get $\mu = 0*0.352 + 1*0.432 + 2*0.188 + 3*0.028$.
Step 7 :Calculating the above expression, we get $\mu = 0 + 0.432 + 0.376 + 0.084 = 0.892$.
Step 8 :So, the mean of the random variable $x$ is $0.892$.
Step 9 :Finally, we need to find the standard deviation of the random variable $x$. The standard deviation is a measure of the amount of variation or dispersion of a set of values. The standard deviation $\sigma$ of a random variable $x$ with mean $\mu$ is given by $\sigma = \sqrt{\sum (x - \mu)^2 P(x)}$.
Step 10 :Substituting the given values into the formula, we get $\sigma = \sqrt{(0 - 0.892)^2*0.352 + (1 - 0.892)^2*0.432 + (2 - 0.892)^2*0.188 + (3 - 0.892)^2*0.028}$.
Step 11 :Calculating the above expression, we get $\sigma = \sqrt{0.281 + 0.043 + 0.042 + 0.066} = \sqrt{0.432}$.
Step 12 :So, the standard deviation of the random variable $x$ is $\sqrt{0.432}$, or approximately $0.657$ when rounded to three decimal places.