Quantitative Data Analysis Flashcards
List the four types of quantitative data analysis approaches:
- Experiments
- Quasi-Experiments
- Evaluations
- Surveys
What are experiments?
When the researcher manipulates one variable to see if it affects another variable.
What do quasi-experiments seek to determine?
Whether one variable affects another variable, but research participants are not randomly assigned to groups or no control is offered.
! Findings cannot be generalised to other contexts !
What are evaluations?
- They address questions about the effects of a policy or proposed action
What are surveys?
- Feature an instrument or questionnaire which participants fill out themselves or with a researcher worker present.
Define what secondary data analysis is:
- Analysing data collected by other previous researchers.
- Already been obtained and are readily accessible from other sources.
What kind of data sets are used in secondary data analysis?
- Cross-sectional:
Focused on a particular moment in time. - Longitundinal:
This is about the same group of research participants at different points in time.
*Difficult to collect due to the vast time commitment and resoruces to follow up with same research participants
What are four advantages of secondary data?
- It’s economical - saving time and cost
- Helps make processing primary dtata more specific as gaps and limitations with the aid of secondary data.
- Helps increase understanding of the issue
- Provides framework for comparison of data gotten by the research.
What are four disadvantages of secondary data?
- Personal bias - info from newspapers, magazines, personal diaries may have personal bias
- Format - data must be available in the required format
- Availability - important to make sure required data is available before proceeding further with study
- Validity and reliability - vaildity of data may vary from source to source
Define a ‘variable’ in research:
They are features or qualities that change.
Name and define two types of variables:
- Independent variable (the cause) - the one which is assumed will cause results. It is manipulated to determine influence on dependent variable.
- Dependent variable (effect) - the one tested to see effect of the independent variable on the variable. The number of dependent variables in the experiment should be increased to obtain stronger and more concrete effects.
Variable are often categorised as either discrete variables or continuous variables.
What are the four types of measuring variables
- Nominal scale - data arranged into categories that are not ranked or ordered in a way
- Ordinal scale - Data arranged in categories that are ranked or ordered in some way
- Interval scale - Data is continuous with each case and able to set on any value within a set range
- Ratio scale - quantitative scale where there is a true zero and equal intervals between neighbouring points. Ratio data features to an absolute zero or a point at which there is a complete absence of quantity of interest.
**only ratio data allow researchers to express relationships between observation as consistent ratios.
What is a population in terms of quantitative data analysis?
- The whole group that you want to draw conclusions from. Researchers want to know about populations but they do not have data for evey person or item in the population thus they collect data from a sample of the population.
What is a sample?
- Smaller selection of individuals or units within the population.
Researchers may then use knowledge of the characteristics of the sample to draw more general inferences on the characteristics of the population.
What is statistical inference?
- When we use data received from a sample to draw concusions about a population.
