UNIT 1: Describing Data

Statistics

Study of methods to describe and measure aspects of nature from samples.

Estimation

Process of inferring an unknown quantity of a population using sample data.

Parameters

Quantities that describe populations, such as averages and measures of variation.

Statistical hypothesis

Specific claim regarding a population parameter evaluated using data.

Population

All the individuals of interest in a study.

Sample

Subset of individuals taken from a population.

Sampling Error

Chance of difference between an estimate and the population parameter caused by sampling.

Bias

Systematic discrepancy between estimates obtained through repeated sampling.

Random sampling

Each member of a population has an equal and independent chance of being selected.

Sample of convenience

Collection of individuals easily available to the researcher.

Volunteer bias

Bias from systematic differences between volunteers and the population.

Variable

Characteristics that differ among individuals or sampling units.

Data

Measurements of one or more variables made on a sample of individuals.

Categorical variables

Qualitative characteristics that do not correspond to a degree of difference on a numerical scale.

Numerical variable

Quantitative measurements that have magnitude on a numerical scale.

Explanatory variable

Variable that predicts or affects another variable.

Response variable

The variable that is affected in an experiment.

Frequency

Number of observations having a particular value.

Frequency distribution

Number of times each value of a variable occurs in a sample.

Probability distribution

Distribution of a variable in the population.

Normal distribution

Approximated probability distribution resembling a bell curve.

Experimental study

Researcher assigns different treatments randomly to individuals.

Observational study

Researcher observes without control over treatment assignment.

Confounding variable

Variable that distorts the causal relationship between measured variables.

Qualitative data

Data that represent qualities or categories without numerical values.

Nominal data

Qualitative data with no natural order to categories.

Ordinal data

Qualitative data with ordered categories.

Quantitative data

Data representing measurable quantities that can be counted or measured.

Discrete data

Countable values, usually integers.

Continuous data

Any value within a range.

Cumulative frequency

Running total of all frequencies.

Histogram

Graphical bars showing the distribution of quantitative variables.

Stem-Leaf plot

Shows actual values in structured rows.

Measures of Central Tendency

Methods to describe the center of a data set: mean, median, mode.

Mean

Arithmetic average of a set of data points.

Median

Middle value of a data set, also known as the 50th percentile.

Mode

Most frequently occurring value in a data set.

Weighted mean

Mean that accounts for unequal importance of values.