Data Analysis
What is the mean?
This is the average of a set of numbers.
What is supervised learning?
This type of learning trains a model using examples with answers.
What is a bar chart?
This type of graph uses bars of different lengths to show data.
What is Python?
This programming language is known for its simple syntax and is popular in data science.
In data science, what does "NaN" stand for when representing missing or undefined values in a dataset?
Not A Number
What is the median?
Sorting data in ascending order helps you easily find this middle value.
What is classification?
A model that predicts “yes” or “no” is performing this kind of task.
What is a line chart?
This type of graph is great for showing trends over time.
What is a relational database?
SQL is used to work with this kind of database.
What is a question?
This is the first step in most data science projects: asking a ___.
What is a histogram?
This chart type groups data into bins to show how often values occur.
What is linear regression?
This common algorithm finds a line that best fits the data.
What is a scatter plot?
This type of plot uses dots to show how two variables relate.
What is a comma?
CSV files separate values using this character.
What is a visualization?
This type of chart, graph, or picture helps you see patterns in data.
What is variability (or spread)?
This value describes how spread out data is, often measured by standard deviation.
What is overfitting?
Splitting your data into training and testing sets helps avoid this problem.
What is a pie chart?
This chart type is made of slices to show proportions.
What is Google Colab?
This Google product lets you write and run Python in your browser.
What is data splitting (or train/test split)?
This common process divides data into separate sets to train and test a model’s performance.
What is correlation?
This type of analysis looks at how two variables move together.
What is a random forest?
This tree-based method builds many decision trees and takes a vote.
What is a legend?
This key element of a chart explains what the colors or shapes mean.
What is data cleaning (or wrangling)?
This is the process of making messy data ready to analyze.
What are the three main components of the "data science pipeline"?
Data collection, data cleaning/preprocessing, and modeling.