Step 1: General properties of chi-square distribution.
The chi-square distribution is widely used in hypothesis testing, especially in tests of independence and goodness of fit.
It is defined only for non-negative values.
Step 2: Important characteristics.
- The chi-square distribution starts at 0 (it cannot take negative values).
- It is positively skewed and not symmetrical, though it approaches normal distribution as the degree of freedom increases.
- The mean of a chi-square distribution is equal to its degrees of freedom ($df$).
- The variance of chi-square distribution is equal to $2 \times df$.
Step 3: Check each statement.
- (A) Correct, chi-square starts at 0.
- (B) Incorrect, it is not symmetrical, it is skewed.
- (C) Correct, mean = df.
- (D) Incorrect, variance is not equal to df.
- (E) Correct, variance = 2 $\times$ df.
Step 4: Conclusion.
Thus, the correct combination is A, C, and E.