Agresti & Franklin - Chapter 1 

Statistics: the art and science of learning from data.

Data: the information we gather with experience and surveys.

Design: What do I want to study and how do I get the data I need to answer my question

Description: How do I present the data found

Inference: How do I use this data to make a prediction (usually on a larger scale)

Subjects: entities you measure in a study

Population: set of all the subjects in interest

Sample: subset of the population from whom we have data, often randomly selected.

Descriptive statistics: refers to methods for summarising the collected data. Usually consists of graphs and numbers (averages, percentages, etc.)

Inferential statistics: refers to methods of making decisions or predictions about a population, based on the data obtained from a sample of that population.

Parameter: nummerical summary of the population

Statistic: nummerical summary of a sample taken from the population

Random sampling: way of sampling used to make the sample as representative to the population as possible.

Margin of error: a measure of the expected variability between one sample and the next sample

Very likely → 95% confidence interval (out of 100 times, 95 correct)

n → how many subjects in a sample

Statistically significant: if the sample percentage falls out of the margin of error, the result of the conducted study is likely not caused by random variation.