Data Collection Methods - ACT Math

Numerical data with meaningful intervals and a true zero. Height, weight, and time are common examples.

Subjects alter behavior because they know they are being observed. Being observed changes how people naturally behave.

Research conducted over a long period to observe long-term effects. Tracks changes in subjects over extended time periods.

Observational study analyzing data from a population at one point in time. Provides a snapshot of a population at a specific moment.

A parameter describes a population; a statistic describes a sample. Parameters are true values; statistics are estimates from samples.

Dividing population into clusters and randomly selecting entire clusters. Useful when natural groups exist within the population.

A subset of the population used to infer about the population. It's used when studying the entire population isn't practical.

Numerical data representing counts or measurements. This includes discrete counts and continuous measurements.

They can collect data from a large number of respondents quickly. They're cost-effective and can reach geographically dispersed groups.

Neither participants nor researchers know who receives treatment. This prevents bias from expectations affecting results.

The entire group of individuals or items being studied. This is the total set from which samples are drawn.

A parameter describes a population; a statistic describes a sample. Parameters are true values; statistics are estimates from samples.

To reduce bias and ensure each member of a population has equal chance of selection. This prevents selection bias and improves representativeness.

Neither participants nor researchers know who receives treatment. This prevents bias from expectations affecting results.

Categorical data without a natural order. Examples include gender, color, or brand names.

Dividing a population into subgroups and sampling each subgroup. This ensures representation from all relevant subgroups.

The entire group of individuals or items being studied. This is the total set from which samples are drawn.

A group in an experiment that does not receive the treatment. Used for comparison to measure treatment effectiveness.

To ensure accuracy and quality of data collected. Checks for errors, completeness, and consistency.

A systematic error that leads to incorrect conclusions. It occurs when the sample isn't representative of the population.

Selecting individuals that are easiest to reach. This method is quick but may not represent the full population.

The proportion of respondents who completed the survey. Higher rates indicate more representative results.

To test the feasibility and design of a larger study. It's a small-scale trial run before the full study.

Categorical data with a meaningful order but no fixed intervals. Like rating scales: poor, fair, good, excellent.

A conclusion drawn about a population based on a sample. Uses sample data to make predictions about the whole population.

They can collect data from a large number of respondents quickly. They're cost-effective and can reach geographically dispersed groups.

Consistency in results across different occasions. Reliable data gives similar results when measurement is repeated.

Research conducted over a long period to observe long-term effects. Tracks changes in subjects over extended time periods.

Observational study analyzing data from a population at one point in time. Provides a snapshot of a population at a specific moment.