Which type of sampling has a higher risk of sampling bias according to the notes?
Non-probability sampling has higher bias risk.
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Non-probability sampling has higher bias risk.
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Disproportionate means sample sizes differ from population proportions.
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Cluster sampling selects whole groups.
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Clusters should represent the population.
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Convenience sampling uses easy-to-access participants.
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Purposive sampling selects based on purpose.
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Snowball sampling uses participant referrals.
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Quota sampling fills non-random categories.
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Sampling allows inference about a population.
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Probability sampling uses random selection.
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Simple random sampling gives equal chance to all.
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Systematic sampling selects at regular intervals.
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Stratified sampling selects from subgroups.
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Stratification ensures subgroup representation.
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Proportionate sampling reflects population proportions.
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Disproportionate stratification does not match population proportions.
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Causal hypotheses propose cause and effect.
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Associative hypotheses state relationships; causal hypotheses state cause-effect.
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A hypothesis with multiple variables is complex.
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Statistical significance is not a source of hypotheses.
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General patterns can generate hypotheses.
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The population is the entire target group.
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A sample is a subset of the population.
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A null hypothesis states no relationship or no difference.
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KR-20 is for binary-scored items.
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