Describing the Distribution of Data

Question 1

What are the features of a normal distribution?

Answer 1

A symmetrical distribution of data with ‘well-behaved’ tails

Question 2

When do we refer to the distribution of data as ‘skewed’?

Answer 2

If the data is ASYMMETRIC with many data points in the high or low end of the range, and an uneven tail (long on one side and short on the other), it is SKEWED.

Question 3

What do we mean by ‘kurtosis’?

Answer 3

There is a SYMMETRICAL distribution of data, but with tails which do not taper off (they are heavy tailed or light tailed relative to a normal distribution); there is a wide distribution.

Question 4

If the tail is longer on the right side, what do we call this?

Answer 4

Right-skewed distribution

Question 5

If the tail is longer on the left side, what do we call this?

Answer 5

Left-skewed distribution

Question 6

In a right-skewed distribution, where is the mean?

Answer 6

It is to the right of the peak

Question 7

In a left-skewed distribution, where is the mean?

Answer 7

It is to the left of the peak

Question 8

What term is synonymous with ‘right-skewed’? (Think about a histogram being plotted on a four quadrant coordinate grid.)

Answer 8

Positively-skewed; the long tail is in the positive direction of the number line.

Question 9

What term is synonymous with ‘left-skewed’? (Think about a histogram being plotted on a four quadrant coordinate grid.)

Answer 9

Negatively-skewed; the long tail is in the negative direction of the number line.

Question 10

If the data shows a narrowed normal distribution shape, what do we call this?

Answer 10

Kurtosis

Question 11

A lack of what would cause a narrow normal distribution?

Answer 11

A lack of outliers (the things which normally contribute to the tails on a normal distribution).