Research Process Flashcards
Hypothesis
a testable statement predicting the outcomes of a study
types of hypothesis
Non-directional, directional and null
Non-directional hypotheses
predicts that there will be a relationship between the variables, but does not specify the direction of the relationship
Directional hypotheses
predicts that there will be a specific relationship between the variables
Null hypotheses
any relationship that is found between the variables are purely due to chance
Operationalisation
defining variables to accurately manipulate, measure, quantify, and replicate
Pilot studies
conducted to analyse the technical and financial risks and to assess the feasibility of the study
Standardised procedures
important to ensure that all participants undergo the same procedure. This helps to increase reliability and replicability.
types of Sampling methods
Opportunity sampling, Volunteer sampling & Random sampling
Opportunity sampling
participants are chosen because they are available
Opportunity sampling Strengths
Quicker and easier than other methods
Opportunity sampling Weakness
Likely to be non-representative, as people from the same area may be a biased sample
Volunteer sampling
participants are invited to participate. Those who reply will be part of the sample
Volunteer sampling Strengths
participants are likely to stay committed and would be willing to return for repeated testing
Volunteer sampling Weakness
Sample may be unrepresentative because people who respond may be similar (they may have free time)
Random sampling
all participants are chosen randomly. Could be with a draw, or random number generator
Random sampling Strengths
Sample is likely to be representative of the target population as all type of people has an equal chance of being chosen
Random sampling Weakness
Everyone may not be equally chosen. For example, there could be more girls chosen randomly than boys
Quantitative Data
data in numerical format
Quantitative Data Strengths
objective measure, very reliable, data can be analysed using statistical methods and, data is easy to compare
Quantitative Data Weakness
data interpretation may be subjective. Not representative, generalisable, or reliable
Qualitative Data
data written in a non-numerical format that often expresses a quality or opinion
Qualitative Data Strengths
highly valid, unrequested, but important data is incurred
Qualitative Data Weakness
data interpretation may be subjective. Not representative, generalisable, or reliable
The measure of central tendency
a mathematical way to find the average score from a data set using themode, median,andmean
The measure of spread
a mathematical way to describe the variation within a data set
Standard Deviation
the average difference between each score in the data set and the mean
T-test
a statistical test used to determine any significant difference between the mean scores of 2 groups
Graphs
bar charts, histograms, scatter graphs, and normal distribution curves can be used to provide a visual illustration of the data
