Descriptive methods to portray data visually.

Collecting raw data without interpretation.

Statistical analysis involves collecting, reviewing, and interpreting data to discover patterns and trends.

Random sampling to estimate the future outcomes.

Techniques to test hypotheses and predict future occurrences.

Descriptive statistics summarize data using measures like mean, median, and mode.

Deep machine learning models for data analysis.

Methods to create statistical models based on assumptions.

Gathering data without any analysis.

Summarizing data with simple numerical representations.

Measure the central tendency in data.

Inferential statistics make predictions or inferences about a population based on a sample of data drawn from it.

A population includes all elements from a set of data that meet certain criteria.

A random subset of data from a larger set.

The computed average of a data set.

A statistic summarizing the data variability.

The entire data collected during a study.

All possible outcomes of a statistical model.

A sample is a subset of a population used to represent the population in statistical analysis.

A theoretical value used in predictions.