Statistics: Data Types, Descriptive & Inferential Statistics, Visualization, Data Collection, Census and Sampling

Vocabulary flashcards covering key terms from data types, statistics, data visualization, data collection methods, census, and sampling.

Data

Factual information used for analysis and reasoning (e.g., measurements, statistics).

Descriptive Statistics

The process of collecting, organizing, summarizing, and presenting data.

Inferential Statistics

Using data from a subset (sample) to make generalizations about a larger population.

Population

All subjects being studied.

Sample

A smaller, representative group selected from a population.

Qualitative Data

Descriptive, word-based information (non-numeric).

Qualitative Variables

Variables that place data into distinct categories (e.g., marital status, hair color).

Quantitative Data

Numerical information.

Quantitative Variables

Numeric variables that can be ranked or ordered.

Discrete Variables

Countable values, typically whole numbers (e.g., number of cars sold).

Continuous Variables

Measured values that can take any value within a range (e.g., height, temperature).

Nominal Level

Data categorized without any order (e.g., gender, eye color).

Ordinal Level

Data that can be ordered, but differences between ranks are not precise.

Interval Level

Data that is ordered with meaningful differences, but has no true zero (e.g., Celsius temperature).

Ratio Level

Data with ordered values, meaningful differences, and a true zero (e.g., weight, height, salary).

Measures of Central Tendency

Statistics that identify the center of a data set (mean, median, mode).

Mean

Arithmetic average of a data set.

Median

Middle value when data are ordered.

Mode

Most frequently occurring value.

Measures of Variation

Describe the spread of data (range, variance, standard deviation).

Range

Difference between the maximum and minimum values.

Variance

Average squared deviation from the mean.

Standard Deviation

Square root of the variance; measures spread around the mean.

Measures of Position

Locate a data point's relative position (percentiles, quartiles, standard scores).

Percentiles

Values below which a given percent of data falls.

Quartiles

Dividing data into four equal parts.

Standard Scores

Z-scores indicating how many standard deviations a value is from the mean.

Line Graph

Graph showing trends or changes over time.

Bar Graph

Graph comparing distinct categories.

Pie Chart

Chart showing proportions of a whole (percentages).

Histogram

Frequency distribution of continuous data; bars with no gaps.

Scatter Plot

Plot illustrating the relationship between two variables.

Survey Method

Data collection by asking questions (questionnaire or interview).

Observation Method

Recording behavior as it occurs.

Experimental Method

Data collection under controlled conditions with active manipulation of variables.

Use of Existing Studies

Using documentary or field sources for data.

Registration Method

Using registration records (e.g., car, student, hospital).

Census (Complete Enumeration)

Gaining information from every unit in the population.

Survey Sampling

Obtaining information from units in a selected sample.

Advantages of Survey Sampling

Lower cost, faster, broader scope, and greater accuracy.

Probability Sampling

Sampling where each population element has a known nonzero chance of selection.

Random Sampling

Every distinct sample of size n has an equal chance of being drawn.

Stratified Random Sampling

Population divided into strata; simple random samples drawn from each stratum.

Cluster Sampling

Select clusters and then census every element in the selected clusters.

Systematic Sampling

Select every kth unit from an ordered population, with the first unit chosen at random.