Flashcards · Data Analysis · Free
Data Analysis flashcards, generated for you.
Example Data Analysis study cards to learn from right now — then generate a full set from your own notes (plus a practice quiz) and export to Quizlet or Anki. Free, no account needed.
Example Data Analysis flashcards
What is a dataset in data analysis?
A collection of data points or records, typically organized in rows (observations) and columns (variables), forming the raw material for analysis.
What is the difference between a population and a sample?
A population is the entire set of individuals or items of interest; a sample is a subset selected from the population to represent it.
Define descriptive statistics.
Statistical methods used to summarize and describe the main features of a dataset (mean, median, mode, standard deviation, range).
What is inferential statistics?
Statistical techniques used to draw conclusions about a population based on sample data, including hypothesis testing and confidence intervals.
Explain the concept of a null hypothesis.
A statement assuming no effect or no difference between groups; tested to determine if there is sufficient evidence to reject it in favor of an alternative hypothesis.
What is a p-value and what does it represent?
The probability of observing data as extreme as (or more extreme than) the actual observed data, assuming the null hypothesis is true; lower p-values suggest stronger evidence against the null.
What is correlation and how does it differ from causation?
Correlation measures the strength and direction of a linear relationship between two variables; causation implies one variable directly causes changes in another. Correlation ≠ causation.
What is a confidence interval?
A range of values computed from sample data that is likely to contain the true population parameter with a specified probability (e.g., 95% confidence interval).
Define regression analysis and its primary purpose.
A statistical method modeling the relationship between a dependent variable and one or more independent variables; used for prediction and understanding variable relationships.
What is the difference between parametric and non-parametric tests?
Parametric tests assume data follows a specific distribution (usually normal) and have stricter assumptions; non-parametric tests make fewer assumptions and are distribution-free, used when assumptions are violated.
Make your own Data Analysis study set
Flashcards for related topics
Studying Data Analysis to build with AI? MindloomHQ turns it into real skills — structured courses, agent projects, and certificates.
Explore MindloomHQ →