1. Measures of Central Tendency and Dispersion
Worksheet:
The worksheet 3_Evaluation_of_research_methods.doc can be used as a template for students to evaluate any theory or research study in Research Methods.
Image credit:
Image© dragon_fang, shutterstock.com
Measures of Central Tendency and Dispersion

2. Measures of central tendency

3. Which measure of central tendency?
Worksheet:
The worksheet 3_5_Measures_of_central_tendency.doc accompanies this slide.
The solution can be found on the handout 3_5_Measures_of_central_tendency_answer.doc.

4. Measures of dispersion - range
Measures of dispersion show how the data is spread out.
There are two types of measure of dispersion: range and standard deviation.
The range is a measure of the spread of the dataset. It can
be calculated by subtracting the lowest number in the dataset from the highest number of the dataset.
The range gives an indication of reliability. A small range means the experiment has produced several similar data points.
Range is easily skewed by a single very large or small value.

5. formula for standard deviation:
The standard deviation shows the average distance from the mean of all the data points. It is a measure of variation.
Unlike the range, standard deviation is not distorted by outliers. The measure uses all of the data points to calculate the variation from the mean, so it is a more accurate measurement.
If a dataset for an experiment has a low standard deviation,
it means that all of the data points are close to the mean and
it is a reliable test.
formula for standard deviation:
For example, if you look at
a set of exam results the standard deviation will tell you how different the marks of the whole class are.
Teacher’s notes:
Standard deviation (σ) is calculated by subtracting the mean from every data point and squaring the result, the sum of these results is then found. This is divided by the number of data points there are and the square root is found.

6. Calculate statistical measures

7. Task
Create a paper aeroplane in 2 minutes. Write your name on it CLEARLY
There are no rules apart from that it must be made from paper no larger than A4 

8. Calculating quantitative data
You will now throw your plane.
The distance will be measured and written on the whiteboard next to your name.
You must calculate:
Mean
Mode
Median
Range
How could this data be represented in a graph?

9. Task

10. These distributions are generally classed as normal or skewed.
Data Distributions
If we are plotting frequency data, we may start to see patterns arise in a data distribution.
The larger the data set, the more likely these distributions are to occur.
These distributions are generally classed as normal or skewed.

11. Normal Distribution Data Distributions
Most results cluster around the mean
A few very high and a few very low.
Often called a bell curve
68.26% of people will be within one SD of the mean
95.44% will be within two SD of the mean
99.74% are within three SD.
0.26% will beyond three SD.

12. Think of other examples where we would expect a normal distribution.

13. Skewed Distribution Data Distributions
Not all data will be a normal distribution
Data may cluster around high or low scores, skewing the bell curve
This affects the mean, median and mode

14. Data Distributions Negatively Skewed: A few extreme low scores
A skew towards high scores.
Long tail on the left.
The mode is greater than the mean.
Eg. Results for an easy maths test
Very few students did poorly on the test.
Most scored high, meaning the distribution is skewed to the left.

15. Data Distributions Positively Skewed: A few extreme high scores
A skew towards low scores.
Long tail on the right.
The mean is greater than the mode.
Example: how long people admitted to hospital stay before being discharged.
Very few patients stay for an extended period.
Most are discharged after a few days, meaning the distribution is skewed to the right.

16. Complete the graphs card sort game.
Challenge Task
Complete the graphs card sort game.

17. Answers