Week 8 Flashcards
What does descriptive statistics allow?
Allows the researchers to describe, organise and summarise raw data
What does inferential statistics allow for?
It allows researchers to estimate how reliably they can predictions and generalise their findings based on the data
What are the 3 most common measures of variability?
- range
- variance
- standard deviation
What is standard deviation?
Standard deviation is the square root of the variance- therefore in same units as original measurements
What are the advantages of standard deviation?
- takes all the scores into account
- can be used to interpret individual scores
- standard deviation allows the reader to get a feel for the variation the data contain
- used in calculation of many inferential statistics
What are inferential statistics?
It allows inferences or conclusions to be drawn from data
What does descriptive statistics do?
It summarises data
There are usually 2 purposes for inferential statistics. What were they?
- estimate how well a sample statistic reflects the population parameter
- test hypotheses or predictions about population
What do research hypotheses do?
Shows that there is some specified relationship between dependent and independent variables
What does a null hypotheses do?
Shows that there is no relationship between dependent and independent variables.
It is easier to disprove something than to prove it.
How is trustworthiness/rigor assured in qualitative research?
-Credibility (truthfulness)
-Auditability (consistency)
-Transferability (fittingness/applicability)
-Confirmability (no bias or distortion)
through member checking, audit trails, triangulation
Why is rigor so important?
Need to know methods can be trusted and can have confidence in results, and using them ie
applying in clinical practice
List four quantitative data collection methods
- Physiologic/laboratory-based: Experiments/clinical trials
- Observational: Observing and recording well-defined events (e.g., counting the number of patients waiting in emergency at specified times of the day)
- Questions & self-report scales- questionnaires: -Administering surveys with closed-ended questions questionnaires
- Interviews: face-to face and telephone interviews
Define reliability and validity in relation to measurement error.
-Reliability means: that a measure can be relied upon consistently to give the same result if the aspect being measured has not changed
-Validity reflects how accurately the measure yields information about the true or real
variable being measured.
A measure is valid if it measures correctly & accurately what it is intended to measure
Descriptive statistics allow researchers to?
describe, organise & summarise raw data
Inferential statistics allow researchers to?
Estimate how reliably they can make predictions & generalise their findings based on the data
The purpose of descriptive statistics is to?
organize and summarise the data
Name four levels of measurement in quantitative data analysis and briefly define each of these:
- Nominal: discrete categories
- Ordinal: relative ranking
- Interval; specific numerical distance between scores- treated as equal; continuous
- Ratio: as above but has absolute zero
Name and briefly describe the three most common measures of central tendency?
- Mean: average score
- Median: middle score
- Mode: most common score
Briefly describe Cross-sectional studies?
collect all data at one point in time
Briefly describe Longitudinal studies ?
Longitudinal studies collect data at different points in time
Briefly describe Retrospective studies
Retrospective studies collect data on past events
Briefly describe Prospective studies
Prospective studies collect data as they occur
Briefly describe Independent variable
- manipulated variable (cause)
- used to predict outcome of interest ie dependent variable
Briefly describe Dependent variable
- measured variable (effect)
- consequence/presumed effect that changes with change in independent variable
Name two types of validity and briefly define each
-Internal validity: does the independent variable accurately measure what it says it will
measure. Asks whether independent variable really made the difference- refers to
the causal relationship
-External validity: deals with problems of generalisability of findings to other populations and
other environmental conditions
