Select all of the following indicators which would cause you to reject normality for a sample of data. Answer 2 Points \[ \begin{array}{l}\text { A normal probability plot of the data follows a linear pattern. } \\ \text { A normal probability plot of the data follows a curved shape. } \\ \text { The data has four outliers present. } \\ \text { A histogram of the data shows bar heights decreasing from right to left. }\end{array} \]

If you're diving into the delightful world of statistics, a normal probability plot is your trusty compass for assessing normality! When the plot follows a linear pattern, it suggests that your data might just be following that normal distribution vibe. However, if the plot takes on a curved shape, it's waving a big red flag, suggesting the data doesn't conform to normality. And let’s not forget about outliers! If those sneaky outliers are hanging around, they can distort the overall picture of your data distribution, making normality hard to believe. Plus, when you see a histogram with bar heights decreasing from right to left, it's like finding a clue that tells you your data is likely skewed, reinforcing the idea that normality is not in the cards!