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About this document
- Pages
- 4 pages
- Price
- $4 one-time, yours to keep
- Membership
- Included in every plan
- Format
- Subject
- Healthcare, Statistics
- Module
- HLT362V
This assignment covers how to describe a study sample using statistics. It discusses demographic variables, appropriate statistics for different data types, and comparing experimental and control groups. It is for the HLT362V module.
What's inside
- Demographic variables measured at the interval level
- Statistics used to describe the length of labor
- Comparing experimental and control groups
- Marital status mode for subjects
- Generalizability of study findings
- Missing data in income reports
Who it is for: Students taking the HLT362V module. (Undergraduate)
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Summary
Healthcare professionals use statistics to describe and compare study samples. This document shows how to do that, using examples from healthcare studies.
Describing a study sample
It explains how to describe the people in a healthcare study. It asks what demographic variables were measured. It asks what statistics were used to describe the length of labour.
Statistics for length of labour
It asks what statistics were used to describe the length of labour. It asks if the distributions of scores were similar for the experimental and control groups. It asks if the groups were similar in their type of feeding.
Statistics for other variables
It asks what the marital status mode was for the subjects. It asks if a median could be determined for the education data. It asks if the findings from the study can be generalised to Black women.
Mean and standard deviation
It explains how to analyse data as though it were at the interval/ratio level. It asks what the mean post-test empowerment score was for the control group. It asks what the mean baseline and post-test depression scores were for the experimental and control groups.
Key terms
- Demographic variables
- Facts about the people in a study, such as age and income.
- Descriptive statistics
- Numbers that describe the main features of a set of data.
- Median
- The middle value in a set of data.
- Standard deviation
- A measure of how spread out numbers are in a set of data.
- Quasi-experimental study
- A study that estimates the causal impact of an intervention.
- Central tendency
- The middle point of a set of data.
Questions this document helps with
- Which demographic variables are measured at the interval level?
- Which statistics describe the length of labour in a study?
- Can the findings from a study be generalised to a different group?
Summary written with AI from the document's text.
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