Data Analysis - Graphs And Statistics Flashcards
Mean
Adding up all the values in a data set and dividing by the number of values there are
Mode
Most frequently occurring value in a set of data
Two modes = bi-modal
Can have no modes
Median
The central value in a set of data when the values are ranged from lowest to highest
Range
Subtracting the lowest score from the high score
Standard deviation
The larger, the value of standard deviation, the greater the spread or dispersion within the set of data
The lower the value of standard deviation means the data is tightly clustered around them around the main meaning. Participants responded similarly
Standard deviation of 0 means all participants performed the same
Summary table
Measures of central tendency
Measures of dispersion
Provides a clear summary of data
Bar chart
Data is in categories
Columns do not touch
Histogram
Represents data on a continuous scale
Columns touch
The height of the column shows the frequency of values
Scattergram
Used for measuring the relationship between two variables
The pattern of plotted points reveals different types of correlation
Normal distribution
Is symmetrical
The mean, mode and median are all at the same point with very few people at extreme ends
Skewed distribution
A spread of frequency data that is not symmetrical and data is clustered on one end
Positively skewed - Distribution is concentrated towards the left, mean is higher than the median and mode
Negatively skewed - Distribution is concentrated towards the right, mean is lower than the median and mode
Primary Data
Information that has been obtained first hand by a researcher for the purpose of a research project
Secondary Data
Information that has already been collects by someone else and pre-dates the current research project
Meta-Analysis
The process of combining the findings from a number of studies on a particular topic into an overall statistical conclusion
Evaluation - Qualitative Data (STRENGTH)
Rich with detail
Respondent can fully report their thoughts, feelings and opinions
Higher external validity
Evaluation - Qualitative Data (WEAKNESS)
Data often difficult to analyse
Conclusions often rely on subjective interpretations of the researcher (may be subject to bias)
Evaluation - Quantitative Data (STRENGTH)
Easy to analyse
Comparisons can be easily drawn
Data is more objective and less open to bias
Evaluation - Quantitative Data (WEAKNESS)
Much narrower in meaning and detail
May fail to represent real-life
Evaluation - Primary Data (STRENGTH)
Authentic data obtained from participants
Evaluation - Primary Data (WEAKNESS)
Requires time, effort, considerable planning, preparation and resources
Evaluation - Secondary Data (STRENGTH)
Inexpensive
Easily accessible
Quick
Evaluation - Secondary Data (WEAKNESS)
May be variation in the quality and accuracy of the data
May be outdated and incompatible
Data may not match the researcher’s needs
May challenge the validity of any conclusions
Evaluation - Meta-Analysis (STRENGTH)
Can create a larger, more varied sample
Results can be generalised across larger populations
Increases validity
Evaluation - Meta-Analysis (WEAKNESS)
May be prone to publication bias
Researcher may not select all relevant studies
Conclusions will be biased because they only represent some of the relevant data