## What is an acceptable Q-Q plot?

A Q-Q plot is a scatterplot created by plotting two sets of quantiles against one another. If both sets of quantiles came from the same distribution, we should see the points forming a line that’s roughly straight. Here’s an example of a Normal Q-Q plot when both sets of quantiles truly come from Normal distributions.

### What does light tailed Q-Q plot mean?

Left skewed qqplot: Left-skew is also known as negative skew. Light tailed qqplot: meaning that compared to the normal distribution there is little more data located at the extremes of the distribution and less data in the center of the distribution.

#### What is Q-Q plot example?

Q Q Plots (Quantile-Quantile plots) are plots of two quantiles against each other. A quantile is a fraction where certain values fall below that quantile. For example, the median is a quantile where 50% of the data fall below that point and 50% lie above it.

What does heavy tailed Q-Q plot mean?

– Heavy tails. This means that the probability of large numbers if much more likely than a normal distribution. For example for a 12 Page 14 Lecture 10 (MWF) QQplots normal distribution most the observations 98% lie within the interval [¯x − 3s, ¯x + 3s].

What does an S shaped Q-Q plot mean?

Outlier-proneness
8.6.4 Outlier-proneness is indicated by “s-shaped” curves in a Normal Q-Q plot.

## What does a right skewed Q-Q plot mean?

Right-skewed data Below is an example of data (150 observations) that are drawn from a distribution that is right-skewed (in this case it is the exponential distribution). Right-skew is also known as positive skew. On a Q-Q plot right-skewed data appears curved.

### Does Q-Q plot show outliers?

A Q-Q plot is a graphic method for testing whether a dataset follows a given distribution, but it may also be used to determine outliers. The expected values are not following the reference line, indicating the data was not normally distributed, the data points away from the reference lines are suspected outliers.

#### What kind of distribution is being represented in this Q-Q plot?

Normally distributed data The normal distribution is symmetric, so it has no skew (the mean is equal to the median). On a Q-Q plot normally distributed data appears as roughly a straight line (although the ends of the Q-Q plot often start to deviate from the straight line).

How can a Q-Q plot be used to assess the distribution of the random variable?

For a Q-Q Plot, if the scatter points in the plot lie in a straight line, then both the random variable have same distribution, else they have different distribution. From the above Q-Q plot, it is observed that X is normally distributed.

What kind of distribution is represented in this Q-Q plot?