Time consuming and expensive Hard to process large quantity of data
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Sample
A selection of observations taken from a subset of the population which is used to find out information about the population as a whole
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Advantages of a sample
Less time consuming Fewer people have to respond Less data than a census
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Disadvantage of a sample
The data may not be as accurate The data may not be large enough toggle information about the population
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Sampling Units
Individual units of a population
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Sampling Frame
A list of individually named or numbered sampling units
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Simple Random Sample
A sample where every sampling unit has an equal chance of being chosen
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Advantages of Simple Random Sample
Free of bias Easy and cheap to implement Each sampling unit has equal chance of selection
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Disadvantage of Simple Random Sample
A sampling frame is needed Not suitable when the population size is very big
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Systematic Sampling
A method of sampling where the required elements are chosen at regular intervals from an ordered list
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Advantages of Systematic Sampling
Simple and quick to use Suitable for large samples
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Disadvantages of Systematic Sampling
A sampling frame is needed It can introduce bias if sampling frame is not random
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advantages of Stratified Sampling
Sample accuracy reflects the population structure guarantees proportional representation of groups within a population
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Disadvantages of Stratified Sampling
Population must be classified into distinct strata
Selection within each stratum can be time consuming and expensive if sample size is large
A sampling frame is needed
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Stratified Sampling
A method of sampling where the population is divided into mutually exclusive strata and a random sample is taken from each
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The number sampled in a stratum
(Number in stratum/number in population)* overall sample size
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Quota Sampling
A method of sampling where a researcher selects a sample that reflects the characteristics of the whole population
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Advantages of Quota Sampling
Allows a small sample to still represent the whole population No sampling frame required Quick, easy and inexpensive Allows for easy comparison between different groups in the population
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Disadvantages of Quota Sampling
Not random sampling can produce bias Population must be divided into groups which can be costly or inaccurate Non-responces are recorded as such
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Opportunity Sampling
A method of sampling where the people sampled are those who are available at the time the study is carried out and who fit the criteria you are looking for
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Advantages of Opportunity Sampling
Easy to carry out Inexpensive
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Disadvantages of Opportunity Sampling
Unlikely to provide a representative sample Highly dependent on individual researcher
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Quantitative Variables/Data
Variables or data associated with numerical observations
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Qualitative Variables/Data
Variables or data associated with non-numerical observations
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Continuous Variable
A variable that can take any value in a given range
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Discrete Variable
A variable that can take only specific values in a given range
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Class Boundaries
The maximum and minimum values that belong in each class
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Midpoint
The average of the class boundaries
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Class Width
The difference between the upper and lower class boundaries
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Interpercentile range
The difference between the values for 2 given percentiles.
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Cleaning the data
The process of removing anomalies from a data set.
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bivariate data
Data which has pairs of values for two variables
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Correlation
A measure of the linear relationship between two variables
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regression line
a line of best fit, y \= a+bx
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mutually exclusive events
events that have no sample points in common , P(A or B) \= P(A) + P(B)
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independent events
The outcome of one event does not affect the outcome of the second event , P(A and B) \= P(A) x P(B)
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tree diagram
A diagram used to show the total number of possible outcomes
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probability distribution
Describes the probability of any outcome in the sample space.
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binomial distribution
When there are a fixed number of trials There are 2 possible outcomes (success or failure) There is a fixed probability of success The trials are independent of each other
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the null hypothesis
The hypothesis you assume to be correct
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alternative hypothesis
Tells us about the parameter if your assumption is wrong
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critical region
the area in the tails of the comparison distribution in which the null hypothesis can be rejected
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mutually exclusive
Events have no outcomes in common, they can't happen at the same time
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independent
When one event has no effect on another
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If events A and B are independent…
P(A intersection B)= P(A)x P(B)
P(A|B)=P(A)
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If events A and B are mutually exclusive
P(A intersection B)= 0
P(A union B)= P(A)+P(B)
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When A and B are not mutually exclusive, P(A union B)=
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