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
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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)
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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)
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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)

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5
Q

State how continuous data is presented

A

Histogram:
- No gaps between bars

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