Definitions Flashcards
DATA
Raw information from which statistics are created
POPULATION
The pool from which a statistical sample is drawn. eg. total number of tech start ups in Asia
SAMPLES
Samples are units collected from the statistical population
SYSTEMATIC SAMPLING
Systematic sampling is where units are collected at regular intervals eg. every 10th person.
STRATIFIED SAMPLING
Dividing population into strata (SUB GROUPS) and then selecting units from each strata. Random samples are then taken from each strata, normally in proportion to the actual percentage of occurrence of the strata in the population.
CLUSTER SAMPLING
Cluster sampling begins by dividing population into clusters. eg suburbs. Then randomly select clusters. Every unit in the clusters selected are included.
CATEGORICAL DATA
Categorical variables are variables that put them into categories, eg. male/female, black/white, age group.
NUMERICAL DATA
Numerical data is data that can me measured such as time, height, weight or amount.
DISCRETE DATA
A discrete variable is one where data is counted eg. How many eggs a hen lays each day. The variable can never be negative, and there will never be half an egg. All numbers can be written down, and are whole numbers. Can be qualitative or quantitative.
CONTINUOUS VARIABLE
A continuous variable is where data is measured. How many litres of milk will a cow give daily.
ORDINAL DATA
Ordinal measure of data is where data is arranged in order, however differences between data have no meaning. eg on a scale of 1-10 how happy are you.
QUANTATTIVE
Quantitative variable has a value or numerical measurement.
QUALITATIVE
Qualitative variable describes an individual by placing it into a category or group, eg male or female.
SIMPLE RANDOM SAMPLE
Sample taken from a population randomly where each unit has the same chance of being selected.
REPRESENTATIVE
A representative sample is a sample that represents the population.
BIAS (Statistics)
The opposite of representative, this is where there is bias in a sample.
Co-efficient of variation.
CV= Sample mean / sample standard deviation X 100%. Used to compare the spread of two different data types. eg. pounds to rupees.
Variance in regards to standard deviation.
The variance tells us the square of standard deviation.
Descriptive statistics.
The explanation of data from a sample through the use of graphs and other descriptive tools. eg averages, modes, etc
Statistics
Collection Organisation Analysis Interpretation of DATA
Inferential statistics
Using the data from a sample to infer information about a population.
Sampling frame
List of individuals that make up the sample.