Stat And Prob Flashcards
data set contains all members of a specified group (the entire list of possible data values). The population refers to the whole group under study or investigation. In research, the population does not always refer to people. It may mean a group containing elements of anything you want to study, such as objects, events, organizations, countries, species, organisms, etc.
Population
is a subset taken from a population, either by random sampling or by non-random sampling. A sample is a representation of the population where it is hoped that valid conclusions will be drawn from the population. This is a part of a population determined by sampling procedures where its size is determined as n.
Sample
Data collected from entire population
Parameter
Data collected from a sample of the entire population
Statistics
is a statistical sampling or testing error caused by systematically favouring some outcomes over others.
Bias
This strategy best fits when the researcher’s main objective is to have a good level of precision.
If a population is small enough and the researchers have the appropriate resources, it is possible to use the entire population as a sample. A small population of around 200 elements or less provides data on all individuals to achieve the desired level of precision.
Using a census for small populations
can be used as a guide for the new study. However, it is recommended to review the procedures done in the previous studies to avoid repeating errors.
Using a sample size of a similar study
A researcher may use published tables, however, it must be aligned with the chosen topic and should be consulted by a statistician.
Using Published Tables For Fixed and Predetermined Criteria
This can also be used in determining the number of samples of a population given a specific margin of error.
Slovin’s formula
is the number of samples
n
is the number of population
N
is the margin of error
e
This is a sampling procedure where every element of a population is given an equal chance of being selected.
Probability sampling
This is a sampling procedure where not every element of the population is given an equal chance of being selected as sample.
Non probability sampling
This sampling technique gives every element of the population an equal chance of being chosen to be part of the sample.
Example: Fishbowl Sampling
Simple random sampling
In this type of random sampling, every kth element of the population is selected until the desired number of elements in the sample is obtained. The k is calculated by dividing the number of elements in the population by the desired number of sample.
Systematic random sampling
This sampling technique divides the population into subgroups called strata and then selects sample randomly from each stratum. ___________ is the process of creating subgroups in a dataset according to various factors
Stratified random sampling
The population is divided into clusters. From these clusters, a random sample is drawn. All the elements from the sample cluster will make up the sample.
Cluster sampling
In this sampling technique, the researchers’ convenience is the primary concern in using this method.
Convenience sampling
It allows the sampler to decide who will or will not be included in a sample.
Judgement sampling
The sample composition must reflect the makeup of the population on some preselected characteristics (gender, educational attainment, race, age, etc.) and it often has a nonrandom component.
Quota sampling
states that the sampling distribution of the mean approaches a normal distribution, as the sample size increases.
Central limit theorem
measures the degree of accuracy of the sample mean as an estimate of the population mean. It is also known as the standard deviation of the sampling distribution of the sampling mean.
Standard error of the mean
