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Representing and Interpreting Data (Samples and Populations (Planning a…
Representing and Interpreting Data
Samples and Populations
Collecting Data
Information or data is always being collected
Different organisations collect different types of data
Once data is collected, it is organised, analysed and interpreted
Survey is a process of collecting data
If every person in an area participates in a survey, it is called census
Sample is when population is randomly selected
Surveys
Frequently used to collect data.
Telephone Interviews
Self Administered Questionnaires
Personal Interviews
Questionnaires
Designed to keep collected data easy to analyse
Closed questions are when responds are within category given
Open questions are when the answer has no boundaries
Planning a Questionnaire
Jargon, slang and abbreviation should be avoided
4 Questions can't be vague
Purpose of questionnaire
Avoid bias and emotional language and double barrel
Questions should flow to one another
Don't ask questions with leading answers
Selecting Samples
Random sampling technique
Primary and Secondary Data
Primary Data
Data that only you have collected. No one has access to it unless it is published
Observation
Observing people, places or things to get results
Simulation
Experiments such as rolling a die
Measurement
Involves using some measuring device to collect data
Surveys
Involve designing a questionnaire to interview people
Experiment
Generally conducted when an experiment data is quantitative
Secondary Data
Data that has already been collected by someone else
Organising and Displaying Data
Examining Data
Once data is collected, it has to be organised
Anomalies in the data will be highlighted
Outliers can affect the result of the data
Frequency Tables
Organising the raw data into a frequency table is the first step in allowing us to see trends in the data
It is necessary to group the data into class intervals if single entries are too much
Size of class interval should lead up to between 5 and 10 groups being formed
Class intervals are set so that each score belongs to one group only
Column Graphs
The data of a frequency table can be displayed as a special column graph. A histogram
Characteristics of a histogram
All columns are equal in width
No gaps are left between columns
Each column straddles an x-axis score; that is, the column starts and finishes halfway between scores
Generally, a half interval is at the beginning and end of the graph. The first score is one unit in from the frequency y-axis
Measures of centre
Median
Middle number
All numbers have to be in increasing order for the median to be calculated
number of scores + 1
÷
2
Mean
Average
total of score(frequency value)
÷
total frequency value
Mode
Most occuring number
Measures of spread
Range
highest score - lowest score