Google Data Analytics Course 4 Glossary

A/B Testing

The process of testing two variations of the same web page to determine which page is more successful at attracting user traffic and generating revenue

Completeness

The degree to which the data contains all desired components or measures

Confidence Interval

A range of values that conveys how likely a statistical estimate reflects the population

Confidence Level

The probability that a sample size accurately reflects the greater population

Consistency

The degree to which data is repeatable from different points of entry or collection

Cross-field Validation

A process that ensures certain conditions for multiple data fields are satisfied

Data Constraints

The criteria that determine whether a piece of a data is clean and valid

Data Integrity

The accuracy, completeness, consistency, and trustworthiness of data throughout its life cycle

Data Manipulation

The process of changing data to make it more organized and easier to read

Data Range

Numerical values that fall between predefined maximum and minimum values

Data Replication

The process of storing data in multiple locations

Data Transfer

The process of copying data from a storage device to computer memory or from one computer to another

DATEIF

A spreadsheet function that calculates the number of days, months, or years between two dates

Estimated Response Rate

The average number of people who typically complete a survey

Hypothesis Testing

A process to determine if a survey or experiment has meaningful results

Mandatory

A data value that cannot be left blank or empty

Margin of Error

The maximum amount that the sample results are expected to differ from those of the actual population

Population

All possible data values in a dataset

Random Sampling

A way of selecting a sample from a population so that every possible type of the sample has an equal chance of being chosen

Regular Expression/RegEx

Sample

In data analytics, a segment of a population that is representative of the entire population

Sampling Bias

Overrepresenting or underrepresenting certain members of a population as a result of working with a sample that is not representative of the population as a whole

Statistical Power

The probability that a test of significance will recognize an effect that is present

Statistical Significance

 The probability that sample results are not due to random chance

Unbiased Sampling

When the sample of the population being measured is representative of the population as a whole

Validity

The degree to which the data conforms to constraints when it is input, collected, or created

VLOOKUP

A spreadsheet function that vertically searches for a certain value in a column to return a corresponding piece of information