Core Chapter 11: Sampling and Data Flashcards
1
Q
State the 4 types of sampling errors
A
- Sampling error: characteristic of sample differs from characteristic of population (occurs even in samples randomly selected to avoid bias)
- Measurement error: errors in measurement at data collection stage
- Coverage error: sample does not accurately represent population (small or biased sample size)
- Non-response error: when large number of sample choose not to respond to survey
2
Q
State the 4 types of sampling methods
A
- Simple random sampling: Drawing lots/numbering population and using random number generator to select sample
- Systematic sampling: selecting members of population at fixed random intervals
- Convenience sampling: sample selected based on convenience of sampler
- Stratified/quota sampling: when population can be divided into sub-groups, and number of those selected from each sub-group correlates to the proportion of each sub-group relative to the entire population
(Stratified sampling: if individuals from each strata are randomly selected)
(Quota sampling: if individuals from each strata are specifically selected)
3
Q
State the 2 types of data
A
- Categorical data: data divided into categories
- Quantitative data: data involves numerical values
(Discrete quantitative data: exact number values obtained by counting)
(Continuous quantitative data: any numerical value within a certain range obtained by measuring)
4
Q
State how discrete numerical data can be presented differently using a column graph
A
Column graph
- Gaps between bars
- Mode can be identified
- Can have symmetric distribution, or be negatively or positively skewed, and can have outliers
- For data with many different data values with low frequencies: grouped discrete data (frequency of classes and modal class are identified)
(can be divided into class intervals)
5
Q
State how continuous data is presented
A
Histogram:
- No gaps between bars