Foundations
Population, sample, parameter, statistic, descriptive statistics, and inference.
Statistics flashcards and practice quiz
Statistics Basics Flashcards and Practice Quiz
Review introductory statistics terms, data types, measurement levels, sampling methods, study designs, descriptive statistics, and inference concepts with cleaned definitions and quick practice questions.
- 53 cleaned study cards
- Flashcard and quiz modes
- Search and category filters
- Links to deeper statistics help
- Core vocabulary Population, sample, parameter, statistic, data, and variables.
- Data types Qualitative, quantitative, nominal, ordinal, interval, and ratio.
- Study design Sampling, experiments, observational studies, treatments, and blocks.
- Inference basics Sampling distributions, standard error, confidence intervals, and p-values.
Practice Statistics Terms
Use the flashcards for quick review, then switch to quiz mode to check whether the definitions are sticking.
Foundations
1 of 53
Statistics
The science of collecting, organizing, analyzing, and interpreting data to estimate values, answer questions, and make informed conclusions.
Definition hidden.
Quiz
Question 1
What This Practice Set Covers
These cards are designed for introductory statistics review before you move into hypothesis testing, regression, ANOVA, SPSS, R, Excel, or Stata assignments.
Data and Measurement
Variables, data types, nominal, ordinal, interval, ratio, and common examples.
Sampling and Design
Random, systematic, stratified, cluster, convenience, experiments, and blocking.
Descriptive Statistics
Mean, median, mode, range, IQR, outlier fences, and z-scores.
Inference
Sampling distributions, standard error, confidence intervals, alpha, and p-values.
Symbols
Common symbols such as population mean, sample mean, standard deviation, and p-value.
Stuck on the Actual Assignment?
Flashcards help with vocabulary. If your assignment includes calculations, software output, a dataset, or a written interpretation, send the full task for a quote.
Statistics Basics Card Library
Search engines and students can still read the full set even without the interactive tool.
Statistics
The science of collecting, organizing, analyzing, and interpreting data to estimate values, answer questions, and make informed conclusions.
Population
The complete group of individuals, objects, or observations that share the characteristic being studied.
Sample
A subset of the population selected for study.
Parameter
A numerical characteristic that describes an entire population.
Statistic
A numerical characteristic that describes a sample.
Descriptive Statistics
Methods used to collect, organize, summarize, and present data with tables, charts, and numerical measures.
Inferential Statistics
Methods used to draw conclusions about a population from information collected in a sample.
Data
Observed values collected from individuals, objects, or events. The characteristics being observed are variables.
Variable
A characteristic or attribute that can take different values, such as age, height, major, income, or gender.
Qualitative Variable
A variable that describes categories or labels rather than numerical amounts, such as eye color or favorite movie.
Quantitative Variable
A variable that takes numerical values, such as height, weight, income, time, or number of siblings.
Discrete Variable
A quantitative variable with a finite or countable set of possible values, usually obtained by counting.
Continuous Variable
A quantitative variable that can take infinitely many values within an interval, usually obtained by measurement.
Levels of Measurement
The four common measurement levels are nominal, ordinal, interval, and ratio.
Nominal Level
Data values are labels or categories with no meaningful order, such as hair color or blood type.
Ordinal Level
Data values have a meaningful order, but the differences between positions are not measured consistently.
Interval Level
Quantitative data with meaningful order and differences, but no true zero point, so ratios are not meaningful.
Ratio Level
Quantitative data with meaningful order, differences, and ratios because the scale has a true zero point.
Random Sampling
A sampling method that uses chance so members of the population have a known chance of being selected.
Systematic Sampling
A sampling method that selects every kth member from an ordered list after a starting point is chosen.
Stratified Sampling
A sampling method that divides the population into strata, then samples from each stratum.
Cluster Sampling
A sampling method that divides the population into clusters, randomly selects clusters, and studies all or some members in those clusters.
Convenience Sampling
A sampling method that selects individuals because they are easy to access, which can create bias.
Observational Study
A study in which researchers observe or measure variables without deliberately applying a treatment.
Experiment
A study in which a treatment is deliberately applied to experimental units to observe its effect on a response.
Treatment
The condition, intervention, or factor level applied to experimental units in an experiment.
Response Variable
The outcome measured or observed in a study or experiment.
Experimental Unit
The person, animal, object, or item that receives a treatment in an experiment.
Completely Randomized Design
An experimental design in which treatments are assigned to experimental units completely at random.
Randomized Complete Block Design
An experimental design in which similar units are grouped into blocks before treatments are randomly assigned within each block.
Primary Data
Data collected directly for the current study or research question.
Secondary Data
Data that already exist because they were collected earlier for another purpose.
Population Distribution
The distribution of a variable across all members of the population.
Sampling Distribution of the Sample Mean
The distribution of sample means from all possible samples of the same size from a population.
Standard Error of the Mean
The standard deviation of the sampling distribution of the sample mean.
Point Estimate
A sample statistic used as a single-value estimate of a population parameter.
Confidence Interval
An interval estimate built from a point estimate, critical value, and standard error to describe uncertainty around a parameter estimate.
Critical Value
A cutoff value from a probability distribution used in confidence intervals and hypothesis tests.
Confidence Level
The long-run percentage of confidence intervals that would contain the true parameter if the same method were repeated many times.
Level of Significance
The probability threshold, usually called alpha, used to decide when sample evidence is strong enough to reject a null hypothesis.
Alpha
The significance level in a hypothesis test, commonly written as alpha.
P-Value
The probability, assuming the null hypothesis is true, of getting a result at least as extreme as the observed result.
Population Mean
The mean of an entire population, commonly represented by the Greek letter mu.
Population Standard Deviation
The standard deviation of an entire population, commonly represented by the Greek letter sigma.
Sample Mean
The arithmetic average of a sample, commonly represented by x-bar.
Sample Standard Deviation
A measure of spread in a sample, commonly represented by s or Sx.
Mean
The arithmetic average of a dataset.
Median
The middle value of an ordered dataset, or the average of the two middle values when there are an even number of observations.
Mode
The most frequently occurring value or category in a dataset.
Range
A measure of spread found by subtracting the minimum value from the maximum value.
Interquartile Range
A measure of spread found by subtracting the first quartile from the third quartile.
Outlier Fence
A common rule that flags values below Q1 minus 1.5 times the IQR or above Q3 plus 1.5 times the IQR.
Z-Score
A standardized value showing how many standard deviations an observation is from the mean.
Related Statistics Help
Use Study Tools Responsibly
Use this page to review concepts, prepare questions, and understand your course material. For graded work, follow your institution academic-integrity rules and Statskan service terms.