Descriptive statistics

Measure of central tendency.

The statistical average.

Add up all the scores then divide by how many there are. EG: 2 + 2 + 2 = 6 / 3 = 2. 

STRENGTHS

• Makes use of all the data.

WEAKNESSES

• Affected by extreme scores.

Measure of central tendency.

The middle value after data has been ordered. EG: 1 2 3 4 5. If there are 2 numbers then add them and divide by 2. EG: 1 2 3 4 5 6 = 3 + 4 = 7 / 2 = 3.5

STRENGTHS

• Unaffected by extreme scores.
• Can be used on ranked data.

WEAKNESSES

• Doesn't work well on small sets of data - not representative.

Measure of central tendency.

The most commonly occurring value. EG: 1 2 2 3 3 4 4 4 .

STRENTHS

• Unaffected by extreme scores.
• Easy to calculate.

WEAKNESSES

• Can be affected dramatically by small changes.
• Tells us nothing about other data.
• May be more than 1.  

Measure of dispersion.

The difference between the highest and the lowest scores in a set of data. Minus the smallest from the biggest. EG: 1 2 3 4 5 = 5 - 1 = 4

STRENGTHS

• Easy to caluculate.
• Gives a basic measure of how data varies.

WEAKNESSES

• Affected by extreme scores.

Measure of dispersion.

Measures how widely spread the data is around the mean - the variability of data. Smaller numbers are better as they show data is closely clustered around the mean while bigger numbers are bad because they show data is widely spread.

STRENGTHS

• Takes account of all data.

WEAKNESSES 

• May hide extreme scores.
• Data cannot be ranked or form catagories.