Terms_and_Definitions

Question 1

A/B Test

Answer 1

A method of comparing two versions of a webpage, feature, or app against each other to determine which performs better.

Question 2

Null Hypothesis (H₀)

Answer 2

Assumes there is no significant difference between the control and test groups.

Question 3

Alternative Hypothesis (H₁)

Answer 3

Assumes there is a significant difference between the control and test groups.

Question 4

P-Value

Answer 4

The probability of observing results at least as extreme as those measured, assuming the null hypothesis is true.

Question 5

Significance Level (α)

Answer 5

The threshold for rejecting the null hypothesis (commonly set at 0.05).

Question 6

Confidence Interval (CI)

Answer 6

A range of values that is likely to contain the true effect size or metric with a given level of confidence (e.g., 95%).

Question 7

Control Group

Answer 7

The group that does not receive the treatment or variant being tested.

Question 8

Test Group

Answer 8

The group that receives the treatment or variant being tested.

Question 9

Randomization

Answer 9

Assigning participants to groups in a way that each participant has an equal chance of being in any group.

Question 10

Power Analysis

Answer 10

A calculation to determine the minimum sample size required to detect a given effect size with sufficient power.

Question 11

Effect Size

Answer 11

The magnitude of the difference between groups (e.g., a 5% increase in conversion rate).

Question 12

Type I Error

Answer 12

Incorrectly rejecting the null hypothesis (false positive).

Question 13

Type II Error

Answer 13

Failing to reject the null hypothesis when it is false (false negative).

Question 14

Bonferroni Correction

Answer 14

A method to adjust significance levels when multiple comparisons are being made.

Question 15

Simpson’s Paradox

Answer 15

A trend appears in different groups of data but disappears or reverses when the groups are combined.

Question 16

Descriptive Statistics

Answer 16

Summarizing and describing the features of a dataset (e.g., mean, median, mode).

Question 17

Inferential Statistics

Answer 17

Using a sample to make generalizations about a population (e.g., hypothesis testing, confidence intervals).

Question 18

Mean

Answer 18

The average value of a dataset.

Question 19

Median

Answer 19

The middle value in a dataset when ordered.

Question 20

Mode

Answer 20

The most frequently occurring value in a dataset.

Question 21

Variance

Answer 21

A measure of how much values in a dataset vary from the mean.

Question 22

Standard Deviation

Answer 22

The square root of the variance, representing data dispersion.

Question 23

Z-Test

Answer 23

A hypothesis test for comparing means when the population variance is known.

Question 24

T-Test

Answer 24

A hypothesis test for comparing means when the population variance is unknown.

Question 25

ANOVA (Analysis of Variance)

Answer 25

A test to compare the means of three or more groups.

Question 26

Chi-Square Test

Answer 26

A test for relationships between categorical variables.

Question 27

Linear Regression

Answer 27

A method to model the relationship between a dependent variable and one or more independent variables.

Question 28

Logistic Regression

Answer 28

A regression model used when the dependent variable is categorical.

Question 29

Bayesian Statistics

Answer 29

An approach to statistics that incorporates prior beliefs or evidence.

Question 30

Frequentist Statistics

Answer 30

A traditional approach to statistics based on frequency or proportion.

Question 31

SELECT

Answer 31

A SQL command used to retrieve data from a database.

Question 32

FROM

Answer 32

Specifies the table to retrieve data from.

Question 33

WHERE

Answer 33

Filters rows based on conditions.

Question 34

GROUP BY

Answer 34

Groups rows sharing a property for aggregation.

Question 35

HAVING

Answer 35

Filters grouped rows based on aggregated values.

Question 36

JOIN

Answer 36

Combines rows from two or more tables based on a related column.

Question 37

INNER JOIN

Answer 37

Returns rows with matching values in both tables.

Question 38

LEFT JOIN

Answer 38

Returns all rows from the left table and matching rows from the right table.

Question 39

RIGHT JOIN

Answer 39

Returns all rows from the right table and matching rows from the left table.

Question 40

OUTER JOIN

Answer 40

Returns all rows from both tables, with nulls where no match exists.

Question 41

ORDER BY

Answer 41

Sorts the result set by specified columns.

Question 42

LIMIT

Answer 42

Restricts the number of rows returned in a query.

Question 43

Subquery

Answer 43

A query nested within another query.

Question 44

CTE (Common Table Expression)

Answer 44

A temporary result set used within a SQL query.

Question 45

Pandas

Answer 45

A library for data manipulation and analysis.

Question 46

NumPy

Answer 46

A library for numerical computations.

Question 47

Matplotlib

Answer 47

A library for creating static visualizations.

Question 48

Seaborn

Answer 48

A library for statistical data visualization.

Question 49

Scipy.stats

Answer 49

A library for statistical functions and tests.

Question 50

Statsmodels

Answer 50

A Python module for statistical modeling and hypothesis testing.

Question 51

A/B Test Simulation

Answer 51

A process to mimic test results using random sampling or bootstrapping.

Question 52

Data Visualization

Answer 52

Representing data graphically to communicate insights.

Question 53

Dashboard

Answer 53

A visual interface that displays key performance metrics and data.

Question 54

Power BI

Answer 54

A business analytics tool for creating dashboards and visualizations.

Question 55

Tableau

Answer 55

A software tool for data visualization and business intelligence.

Question 56

Funnel Analysis

Answer 56

A method to track user journey and identify drop-off points.

Question 57

Cohort Analysis

Answer 57

Analyzing behavior by grouping users based on shared characteristics.

Question 58

Customer Journey

Answer 58

The path a customer takes from initial interaction to conversion.

Question 59

Clickstream Data

Answer 59

Data collected about user interactions on a website or app.

Question 60

Hadoop

Answer 60

A framework for distributed storage and processing of large datasets.

Question 61

Telemetry

Answer 61

The collection of data about the usage of a digital product.

Question 62

Data Pipeline

Answer 62

A series of steps to process and analyze data from source to destination.

Question 63

Hypothesis Validation

Answer 63

The process of testing assumptions with data.

Question 64

Exploratory Data Analysis (EDA)

Answer 64

Initial analysis to summarize data characteristics.

Question 65

ETL (Extract, Transform, Load)

Answer 65

A process for collecting, transforming, and storing data.