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The image you've uploaded shows a statistics question regarding skewed distributions. Specifically, it asks about the relationship between the mean and median in a distribution that is skewed to the right with no outliers.

### Question 107:
**If a distribution is skewed to the right with no outliers, which of the following is true?**
- (a) mean < median.
- (b) mean ≈ median.
- (c) mean = median.
- (d) mean > median.
- (e) We can't tell without examining the data.

### Explanation:
When a distribution is **skewed to the right**, the right tail (higher values) is longer than the left tail. This typically results in a mean that is **greater** than the median because the mean is more influenced by the higher values in the tail.

Thus, the correct answer is:
**(d) mean > median.**

Let me know if you need more clarification, or if you'd like to ask anything else!

Here are five related questions to consider:
1. What happens to the mean and median in a left-skewed distribution?
2. How does the presence of outliers affect the mean and median?
3. Can the mean and median be equal in a skewed distribution?
4. Why is the median considered a better measure of central tendency in skewed distributions?
5. How does skewness impact the interpretation of standard deviation?

**Tip:** The median is more resistant to extreme values, which makes it a more reliable measure of central tendency for skewed distributions.

If a distribution is skewed to the right with no outliers, which of the following is true?
(a) mean < median.
(b) mean ≈ median.
(c) mean = median.
(d) mean > median.
(e) We can't tell without examining the data.

Explore the relationship between the mean and median in right-skewed distributions with no outliers. Learn why the mean is greater than the median due to the influence of the longer right tail.

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