Chapter 1 Stats 1 Flashcards
(26 cards)
Census
- observes or measures every member of a population
Adv:
- completely accurate
Dis:
- time consuming, expensive
- cannot be used when the testing destroys the item
- hard to process large quantity of data
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
Adv:
- less time-consuming and expensive
- Few people have to respond
- less data to process than the census
Dis:
- not as accurate
- The sample may not be large enough to give information about small subgroups of the population
What are sampling units
Individual units of a population
What is a sampling frame
List of sampling units, with each unit given an identifying name or number
Simple random sampling
- a unique number is given to the sampling frame and a random number generator is used to get them
Adv: - free of bias
- easy and cheap to implement for small populations and samples
- each sampling unit has a known and equal chance of selection
Dis: - SF is needed
- not suitable for large population
Systematic sample
- required elements are chosen at regular intervals from an ordered list
Adv: - simple, quick, suitable for large samples and populations
Dis:
- sampling frame is needed, can introduce bias if sampling frame is not random
Stratified sampling
- The population is divided into mutually exclusive strata and random samples taken from each
Adv:
- sample accurately reflects the population structure
- guarantees proportional representation of a group within a population
Dis:
- population must be clearly classified into distinct strata
- selection within each strata suffers from the same disadvantages of simple random sample
Quota sampling
- an interviewer or researcher selects a sample that reflects the characteristics of the whole population
Adv:
- allows a small sample to still be representative of the population and no sampling frame is required
- Quick easy and inexpensive, allows for comparison between different groups within the population
Dis:
- bias, population must be divided into groups which can be costly or inaccurate
- non-responses are not recorded
Opportunity sampling
- consists of taking the samples from people who are available at the time the study is carried out and who fit the criteria you’re looking for
Adv:
- easy and inexpensive
Dis:
- Unlikely to provide a representative sample
- highly dependent on individual researcher
Types of data
Quantitative - numerical
Continuous, (time) discrete (no. Of people)
Qualitative - non-numerical
5 weather stations in UK
- leuchars
- Leeming
- Heathrow
- Hurn
- Camborne
3 weather stations in the world
Jacksonville (near Florida)
Bejijng (east China)
Perth (west Australia)
- the only data recorded is: temp, rainfall, pressure, windspeed
what is meant by a population
Collection of individual items
The large data set: daily total rainfall
- amounts less than 0.05 are recorded as ‘tr’ or ‘trace’
- includes snow and hail
The large data set: daily maximum relative humidity
relative humidities above 95% give rise to misty and foggy conditions
The large data set: Beaufort scale
a scale which measures wind speed
- 0 - calm - less than 1 knot
- 1-3 - light - 1 to 10 knots
- 4 - moderate - 11 to 16 knots
- 5 - fresh - 17 to 21 knots
The large data set: daily total sunshine
recorded to the nearest tenth of an hour
The large data set: daily mean wind direction and windspeed
- averaged over 24 hours from midnight to midnight
- mean wind direction is given as a bearing and as cardinal (compass) directions
The large data set: daily mean cloud cover
- measured in ‘oktas’ or eighths of the sky covered by cloud
The large data set: daily mean visibility
- measured in decametres (Dm)
- is the greatest horizontal distance at which an object can be seen in daylight
The large data set: daily mean pressure
- measured in hectopascals hPa
The large data set: what is measured for the uk locations
- temperature
- rainfall
- sunshine
- wind direction and speed
- gust
- humidity
- cloud cover
- visibility
- pressure
explain systematic sampling
- label members or obtain an ordered list
- divide number of members by how many samples are needed
- select first person using random numbers
- select every other person from the list at regular intervals
explain stratified sampling
- give the different members of the group a number
- use random numbers to select the right number of people from each group
