Data Collection Flashcards
What is a population
In statistics, a population is the whole set of items that are of interest
What is an example of a population
For example, the population could be the items manufactured by a factory or all the people in a town. Information can be obtained from a population
What is raw data
Unprocessed information is known as raw data.
What is a census
A census observes or measures every member of a population.
What is a sample
A sample is a selection of observations taken from a subset of the population which is used to find out information about the population as a whole.
Advantage of a census
It should give a completely accurate result
3 disadvantages of a sample
Time-consuming and expensive
Cannot be used when the testing process destroys the item
Hard to process a large quantity of data
3 advantages of a sample
Less time consuming and expensive than
Fewer people have to respond
Fewer data to process than in a census
2 disadvantages of a sample
Fewer people have to respond to give information about small sub-groups of the population
The data may not be as accurate
The size of the sample depends on the required accuracy and available __________. Generally, the larger the sample, the more ________ it is, but you will need greater resources. If the population is very varied, you need a ______ sample than if the population were uniform. Different samples can lead to different conclusions due to the natural ______ in a population.
Resources, accurate, larger, variation
The size of the sample depends on the required accuracy and available resources. Generally, the larger the sample, the more accurate it is, but you will need greater resources. If the population is very varied, you need a larger sample than if the population were uniform. Different samples can lead to different conclusions due to the natural variation in a population.
What is a sampling unit?
Individual units of a population are known as sampling units.
What is a sampling frame?
Often sampling units of a population are individually named or numbered to form a list called a sampling frame.
How does systematic sampling work?
In systematic sampling, the required elements are chosen at regular intervals from an ordered list.
How could systematic sampling work if a sample size of 20 was required from a population of 100?
For example, if a sample of size 20 was required from a population of 100, you would take every fifth person since 100 / 20 = 5.
How does stratified sampling work?
In stratified sampling, the population is divided into mutually exclusive strata (males and females, for example) and a random sample is taken from each. The proportion of each stratum sampled should be the same.
What is a simple formula that can be used to calculate the number of people we should sample from each stratum
The number sampled in a stratum
—————————————————– x overall sample size number in the population
number in stratum
Name 3 advantages of simple random sampling?
Free of bias
Easy and cheap to implement for small populations and small samples
Each sampling unit has a known and equal chance of selection
Name 2 disadvantages of simple random sampling?
Not suitable when the population size or the sample size is large as it is potentially time-consuming, disruptive and expensive.
A sampling frame is needed
Name 2 advantages of systematic sampling
- Simple and quick to use
* Suitable for large samples and large populations
Name 2 disadvantages of systematic sampling
- A sampling frame is needed
* It can Introduce bias if the sampling frame Is not random
Name 2 advantages of stratified sampling
- Sample accurately reflects the population structure
* Guarantees proportional representation of groups within a population
Name 2 disadvantages of stratified sampling
- Population must be clearly classified into distinct strata
- Selection within each stratum suffers from the same disadvantages as simple random sampling
What are the two types of non-random sampling that you need to know?
There are two types of non-random sampling that you need to know:
• Quota sampling
• Opportunity sampling
In quota sampling, an interviewer or researcher selects a sample that reflects the ______ of the whole population. The population is divided into ____ according to a given characteristic. The size of each group determines the ______ of the sample that should have that characteristic. As an interviewer, you would meet people, assess their group and then, after the interview, allocate them into the appropriate quota. This continues until all ____ have been filled.
characteristics, groups, proportion, quotas,
In quota sampling, an interviewer or researcher selects a sample that reflects the characteristics of the whole population. The population is divided into groups according to a given characteristic. The size of each group determines the proportion of the sample that should have that characteristic. As an interviewer, you would meet people, assess their group and then, after the interview, allocate them into the appropriate quota. This continues until all quotas have been filled. If a person refuses to be interviewed or the quota into which they fit is full, then you simply ignore them and move on to the next person.
When data is presented in a grouped frequency table, the specific data values are not shown. The groups are more commonly known as \_\_\_\_\_\_\_. • Class boundaries tell you the \_\_\_\_\_\_\_ and \_\_\_\_\_\_\_ values that belong in each class. • The midpoint is the \_\_\_\_\_\_\_ of the class boundaries. • The class width is the \_\_\_\_\_\_\_\_\_\_\_ between the upper and lower class boundaries.
When data is presented in a grouped frequency table, the specific data values are not shown. The groups are more commonly known as classes. • Class boundaries tell you the maximum and minimum values that belong in each class. • The midpoint is the average of the class boundaries. • The class width is the difference between the upper and lower class boundaries.
