Statistics Flashcards
Data
Information about the characteristics of individuals
Categorical value
Describes a particular characteristic which can be divided into catagories
Quantitive variable
Describes a characteristic which has a numerical value that can be counted or measured
Population
An entire collection of individuals about which we want to draw conclusions
Census
The collection of information from the whole population
Parameter
A numerical quantity some aspect of a population
Sample
A group of individuals from a population
Survey
The collection of information from a sample
Statistic
A quantity calculated from data gathered from a sample, usually used to estimate a population parameter
Types of errors: Sampling Error
Occurs when an analyst does not select a sample that represents the entire population of data (eg. if a survey on political preferences is conducted only among members of a particular political party)
Types of errors: Coverage Error
Sample doesn’t truly represent the population (eg. limited number in sample)
Types of errors: Measurement Error
Inaccuracies of measurement while collecting data (eg. Rounding up/down of data OR asking questions with judgement statements included)
Types of errors: Non - Response Error
Large number selected but not many respond, missing data could lead to bias (eg. Low-income households not responding to a healthcare survey due to lack of internet access or digital devices)
Sampling Techniques: Simple Random Sampling
Every individual in the population has an equal chance of getting selected. Often achieved by using random number/letter generators
Strength: minimizes selection bias, making sample representative of the population
Weakness: Difficult to implement as it requires a complete list pf the population
Sampling Techniques: Systematic Sampling
Members are selected at regular intervals
Strength: Good if population is big and not all members can be reached
Weakness: Can be biased if patterns align with the selection interval.
Sampling Techniques: Convenience Sampling
Easiest to capture people OR people most likely to respond
Strength: Quick and cost-effective.
Weakness: May not represent the entire population accurately.
Sampling Techniques: Stratified Sampling
Dividing groups based on characteristics and random sampling each subgroup
Strength: Ensures representation of all subgroups.
Weakness: Time-consuming and requires detailed population knowledge.
Sampling Techniques: Quota Sampling
Mix of convenience and strata, non random & based on characteristics
Strength: Practical and ensures key subgroups are included.
Weakness: Can introduce bias and lack generalizability.
Types of data
- Categorical: Describes a particular quality or characteristic (eg. brands of toothpaste)
- Numerical/Quantitative data: Has a numerical value
a. Discrete numerical: Usually the result of counting
b. Usually the result of measurement
