CDE4121 Lecture Notes - Lecture 8: Negative Number, Dependent And Independent Variables, Statistical Parameter
MODULE 8: DESCRIPTIVE DATA ANALYSIS
Descriptive statistics:
• Focuses on summarising data from a sample set
• Method of organising, summarising and presenting data in a convenient and informative form
• Uses graphical techniques to present data in an easy format for the reader to extract useful information
• Uses numerical techniques to summaries data
• Use of pie charts, bar graphs etc.
Inferential statistics:
• Derives conclusions about the characteristics of a population, based on information taken from the sample
set Results are generalised / inferred to the population
• Statistical inference is the process of making an estimate, forecast or decision about a population parameter,
based on the sample data
• Can determine the reliability of the statistical inference & establish a degree of confidence (assuming the
sample has been properly chosen)
Numeric (quantitative) variables: have values that
describe a measurable quantity as a number, like "how
many" or "how much"
Continuous variable: is an observation that can take any
value between a certain set of real numbers, or a variable
that has a continuous distribution function, (i.e.
temperature, weight, height)
Discrete variable: is an observation that can take a value
based on a count from a set of distinct whole values (i.e. the number of legs of an animal, number of siblings)
Categorical variables: have values that describe a "quality" or "characteristic" of a data unit, like "what type" or
"which category" – non numerical (i.e. gender, marital status)
Uni-variate statistics: analysing one variable at one time
Bi-variate statistics: analysing two variables at one time
Multi-variate statistics: analysing three+ variables at one time
Describing the data: measures of central tendency (central point of the data) and measures of variability and
dispersion (the spread of the data)
Mean (average):
• the most popular and useful measure of central location
• simple to calculate and interpret
• unduly influenced by extreme observations, therefore the statistic can be a poor measure of central location
• used with discrete and continuous data (more so continuous data)
Median:
• the value that falls in the middle of an ordered set of values (smallest to largest)
• odd set of measurements
• take the middle number
• even set of measurements
• take the average of the two middle numbers
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