Statistics definition
The science of collecting, analyzing, presenting, and interpreting data, and making decisions based on these analyses.
2 main types of statistics
- Descriptive
- Inferential
Descriptive statistics
Consists of methods for organizing, displaying, and describing data by using tables, graphs, and summary measures.
Ex: deaths due to red-light running
Inferential statistics
Consists of methods that use sample results to help make decisions or predictions about a population.
Ex: is anxiety and depression a major problem among teens.
Variable definition
A characteristic under study that assumes different values for different elements.
Observation or measurement
The value of a variable for an element.
Types of variables
- Qualitative
- Quantitative
Types of quantitative variables
- Discrete
- Continuous
Qualitative (or categorical) variable
A variable that cannot assume a numerical value but can be classified into 2 or more nonnumeric categories.
Ex: colour, birthplace, blood type
Quantitative variable
A variable that can be measured numerically.
Ex: child number, height, cars owned
Discrete quantitative variable
Values are countable.
Ex: number of cars, population
Continuous quantitative variable
Can assume any value over a certain interval or intervals.
Ex: weight, length
Cross-section data
Data collected on different elements at the same point in time or for the same period of time.
Time-series data
Data collected on the same element for the same variable at different points in time or for different periods of time.
Population
Consists of all elements whose being studied.
Sample
A portion of the population selected for study.
Why would you use sample over population data?
- Using whole population data is not always feasible.
- We can used sample to make inferences or draw conclusions about a population.
Sampling error
The difference between the result obtained from a sample survey and the result that would have been obtained from the whole population.
Cannot be avoided.
Non-sampling error or biases
Errors that occur in the collection, recording, and tabulation of data.
Can be minimized if questions are prepared carefully and data is handled cautiously.
4 non-sampling errors types
- Selection error
- Non response error
- Response error
- Voluntary response error
Simple random sample
Every member has an equal probability of being selected.
Systematic random sampling
We select every kth person.
Stratified random sample
- Divide the population into subgroups, based on some characteristic.
- A random sample is selected from each group. The number of samples in each group is proportional to-he groups population size.
Cluster sampling
- Divide the whole population into groups called clusters.
- Each cluster is representative of the population.
- A random sample of clusters is selected.
