Studied by 38 people
Things to consider when collecting data
The sample size
whether it’s representative
Whether it’s biased
How to avoid bias
Sampling method or by increasing the sample size
How to collect data
Questionnaires
Interviews
Observations
Surveys
Mean
Total number of all values divided by the number of values
Median
The middle value
Mode
The most common value
Range
The difference between the highest and lowest value
Interquartile range
Upper quartile - lower quartile
Ways to represent quantitive data
Table, bar chart, scatter graph etc
Representing qualitative data
Use a pie chart etc
Examples of bias in surveys
Voluntary response sampling- People have chosen to take the survey
Response bias - The wording makes people not want to answer truthfully
Convenience sampling - the first people to show up
Non response - people don’t reply so their pov is missed
Non random sampling
Voluntary: asking people to do a survey
Convince: Sampling the first people to show up
Pros of grouped data
Makes the data easier to read and understand
Easier to spot patterns and compare data
Cons of grouped data
Lose accuracy of the data as you no longer know the exact values
Calculations made from these will only be an estimate
Laboratory experiments
Researcher has full control of the variables
Easy to replicate
People may react differently to normal under test conditions
Field experiments
Carried out in an everyday environment
Researcher has some control of the variables
Not easy to replicate and it’s hard to control extraneous variables
Natural experiments
Carried out in the everyday environment
Researcher has no/little control of the variable
Reflects real life behaviour
Low validity due to little control of the variables and it’s difficult to replicate
Frequency density equation
Frequency density = Frequency/ class width
Types of misleading diagrams
Pictograms - same symbol and size need to be used for all the diagrams and a key is needed
3d charts - Distort part of the diagram making it difficult to read the values
Colours - Some colours make part of the diagram stand out more, making it seem more important
Lines drawn too thick make it difficult to read information
Axes and scales that can be misleading
A scale that does not start at zero
Missing values on the scales
Axes that are unevenly scales
Axes that are not labelled
Not using a key
Bivariate
Involves measuring two variables
Multivariate
Made up of two or more variables
eg: comparing height, weight, age and shoe size together
cluster sampling
The population is put into random groups, one group is randomly selected and everyone in the group is asked
Census
Collects information from all members of a population
Lower class boundary
The smallest number in the class
Pilot study
A pilot study is a small scale study that is conducted to inform, predict and direct an intended future scale study
Opinion scale
An opinion scale lets people express their feelings on a numbered scale
How to calculate an index number
Current price divided by base year price then x100
Note 
Flashcard (39)