What is the science of managing data called?
Statistics
It involves collecting, organizing, analyzing, and interpreting data to answer questions and help make decisions.
Why do we study statistics?
To critically analyze graphs and results, and make educated guesses (inferences) about the true state of things
This skill is essential in both academic papers and everyday life.
Name the two core areas of statistics.
- Descriptive Statistics
- Inference Statistics
Descriptive statistics summarize complex information, while inference statistics draw conclusions about a population from a sample.
What is Descriptive Statistics focused on?
Summarizing information that would otherwise be too complex to understand
It transforms raw facts into digestible summaries like averages or charts.
What does Inference Statistics focus on?
The relationship between a sample of data and the entire population
It aims to draw reasonable conclusions about the population based on the sample.
What are the two types of data sources?
- Primary Data
- Secondary Data
Primary data is collected by the researcher, while secondary data is collected by someone else.
What is Primary Data?
Data you collect yourself
It allows for tailored questions and methodology but can be time-consuming and expensive to gather.
What is Secondary Data?
Data collected by someone else
It is easier and cheaper to obtain but may require modifying research questions to fit existing data.
What are key sources for economic data?
- OECD
- World Bank
- IMF
- Official government and central bank websites
These organizations provide a wide range of existing data for research.
What is the difference between a parameter and a statistic?
- Parameter: True value for the population
- Statistic: Value calculated from your sample
The statistic is used to estimate the parameter.
What is the ideal sampling procedure?
Random Sample
It ensures every member of the population has an equal chance of being chosen.
What defines a random sample?
- Every member is chosen by chance
- Every member has an equal likelihood of being chosen
- Every possible sample of that size is equally likely
Simple random sampling is a common method for achieving this.
What is Sampling Bias?
When your sample does not accurately represent the larger population
This can invalidate the results of statistical tests.
What is an example of Sampling Bias?
Surveying only subscribers of a blue party newspaper to predict a national election outcome
This introduces systemic bias, making results invalid for the whole population.
What does Validity ask in a study?
Does the study measure what it is supposed to measure?
Bias harms validity.
What does Reliability ask in a study?
If you repeat the measurement, will you get the same results?
Larger samples generally lead to more reliable results.
