Section B → Types of Data, Preparation, Collection 📊📈📉

Explores different data sources and their benefits, as well as strategies to minimize bias and distortion during data collection in order for one to achieve a full grade/score (9) on her/his/their AQA GCSE Statistics exam!

Standard Deviation of Difference between Means

Standard Deviation of Difference between Means

Formula to calculate the standard deviation of the difference between two sample means.

Raw Data

Data that has not been processed or analyzed.

Categorical Data

Data divided into distinct categories like age groups or colors.

Ordinal Data

Data with a meaningful order but unequal intervals, such as rankings.

Discrete Data

Countable data, like the number of students in a class.

Continuous Data

Data that can take any value within a range, like height measurements.

Ungrouped Data

Data that is not categorized into classes or intervals.

Grouped Data

Data organized into class intervals.

Quantitative Data

Numerical data that can be measured, such as age or weight.

Qualitative Data

Descriptive data like colors or names.

Bivariate Data

Data involving two variables, for example, height vs. weight.

Multivariate Data

Data involving more than two variables, like height, weight, and age.

Primary Data

Data collected firsthand through methods like surveys or experiments.

Secondary Data

Data collected by someone else, such as census data or research reports.

Experimental Data Collection

Gathering data through laboratory, field, or natural experiments.

Sampling Techniques

Various methods used to select a subset of the population for study.

Reliability

The consistency of results obtained from data.

Validity

The accuracy of measurements, also known as bias.

Population

The entire group under study.

Sample Frame

A list of individuals from which a sample is selected.

Sample

A subset of the population used for analysis.

Judgment Sampling

Sampling based on the researcher's judgment.

Opportunity Sampling

Selecting readily available participants for the sample.

Random Sampling

Each member of the population has an equal chance of being selected.

Systematic Sampling

Selecting every nth member from a list.

Quota Sampling

Dividing the population into groups and sampling from each group.

Stratification

Dividing the population into strata before sampling.