1.1 Introduction to Statistics
Statistics: a way to get information from data to make informed decisions.
It is the science of collecting reliable data; analyzing the data using statistical techniques to
extract useful information; and drawing conclusions from the data.
Descriptive statistics
methods of organising, summarising, and presenting data in ways that are useful, attractive and
informative to the reader.
Graphical:
Numerical: mean, median, mode/range, variance, standard deviation
Inferential statistics
process which uses sample statistic to make inference about population parameter
Complaint: weight of Tuna cans less than advertised
Problem: you cannot weigh every single tuna can
Solution: select a random sample, calculate average weights
Statistic: average weight of the cans in the sample
Parameter: average weight of ALL cans in the population
Statistical Inference:
We use sample statistics to make inferences about population parameters.
Therefore, we can produce an estimate, prediction, or decision about a population based on sample data.
Thus, we can apply what we know about a sample to the larger population from which it was drawn!
Rationale:
• Large populations make investigating each member impractical and expensive.
• Easier and cheaper to take a sample and make estimates about the population from the sample.
However:
• Such conclusions and estimates are not always going to be correct.
• For this reason, we build into the statistical inference ‘measures of reliability’, namely confidence
level and significance level.
Significance level: measures how frequently the conclusion will be wrong in the long run.
Confidence level: proportion of times that an estimating procedure will be correct.
Sources of Statistical Data
Published data
-most preferred source of data due to low cost and convenience
• Primary: Published by collectors (e.g. ABS)
• Secondary: Published by non-collectors (e.g. World Bank)
Observational data
Experimental data
Surveys