4.1 Concepts of population, sample, random sample, discrete and continuous data

Key Ideas

Organizing, representing, analysing and interpreting data and utilizing different statistical tools facilitates prediction and drawing of conclusions.
Different statistical techniques require justification and the identification of their limitations and validity..
I can explain the terms: Population, Sample, Census, Survey, Data, Variable, Categorical Variable, Numerical Variable, Random, Bias, Parameter, Statistic, Distribution, Outlier.
I can use a variety of techniques to graph data, both by hand and using technology
I can discuss the reliability of data sources and bias in sampling.
I can determine and Interpret outliers.
I can discuss sampling techniques and their effectiveness.

Key Statistical Concepts

Data comes in two varieties: Categorical and Numerical. We are most interested in Numerical Data, which comes in two types: Discrete Data (you can count) and Continuous Data (you can measure).

From a column graph you can easily tell whether the data is discrete or continuous. "Mind the Gap!!":

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