Data Analysis Fundamentals Quiz

Data is transformed from its raw format to provide information by being gathered, prepared, analyzed, and presented in a usable format.

Exploratory data analysis is a set of procedures designed to create descriptive and graphical summaries of data. The goal is to uncover interesting patterns and insights from the data.

A variable is anything that can change or vary from one occurrence to another. It's a characteristic that can be measured, manipulated, or controlled.

<p>An observation is the recording of values, patterns, and occurrences for a specific set of variables.</p> Signup and view all the answers

<p>A data point is the collection of values that represent a specific observation for all the variables in a dataset.</p> Signup and view all the answers

<p>Nominal (D), Ordinal (E)</p> Signup and view all the answers

<p>Continuous numerical variables are quantitative data that can take on any value within a specific range or continuum. For example, weight, which can be measured with varying decimal values.</p> Signup and view all the answers

<p>Ratio variables are interval variables where a zero value means the complete absence of the measured quantity. For example, if someone has a zero weight, it means they have no weight at all.</p> Signup and view all the answers

<p>Discrete numerical variables represent data that can only take on specific, finite values. For example, the number of visits a patient makes to a doctor, which can only be whole numbers.</p> Signup and view all the answers

<p>Statistics involves the collection and analysis of data using mathematical techniques.</p> Signup and view all the answers

<p>A population refers to a group of similar entities, whether individuals, objects, or events, that share common characteristics.</p> Signup and view all the answers

<p>A sample is a representative subset of the population, chosen to accurately reflect the characteristics of the entire population.</p> Signup and view all the answers

<p>Descriptive statistics aim to describe and summarize the values and observations within a dataset.</p> Signup and view all the answers

<p>Inferential statistics involve collecting, analyzing, and interpreting data from a sample to make generalizations or predictions about the entire population.</p> Signup and view all the answers

<p>A distribution in data analysis refers to the pattern of a variable's frequency or probability over its possible values.</p> Signup and view all the answers

<p>The three key measures of centrality in data analysis are the mean, median, and mode.</p> Signup and view all the answers

<p>Dispersion refers to the variability or spread of data values within a distribution.</p> Signup and view all the answers

<p>The key point to remember is that correlation does not imply causation.</p> Signup and view all the answers

<p>A heat map visually represents the correlation coefficients between multiple variables, indicating the strength and direction of the relationships between them.</p> Signup and view all the answers

<p>Data sets often have incompatibilities, such as missing values, inconsistent formats, or other issues that need addressing.</p> Signup and view all the answers

<p>NaN values represent data that is undefined or cannot be represented, typically indicating missing or invalid data points.</p> Signup and view all the answers

<p>Pandas is a powerful Python library that provides tools for cleaning, manipulating, and analyzing data.</p> Signup and view all the answers

Changing raw data into usable information through gathering, preparation, analysis, and presentation.

Procedures for creating descriptive summaries and graphs of data to find patterns.

Large volume, diverse formats, and often streaming in real time.

Something that can be measured, manipulated, or controlled and varies between different instances.

Recordings of values, patterns, and occurrences for a set of variables.

The set of values for a specific observation.

Categories or names that identify an object, order doesn't matter.

Categories with a meaningful order.

Quantitative values along a range/continuum.

Interval variables with a true zero point (meaning none).

Quantitative values with a specific value from a finite set.

Collecting and analyzing data using mathematical techniques.

The entire group of similar entities.

A representative part of a population.

Summarizing data through measures like mean and median.

Making conclusions about a population based on a sample.

The frequency or probability of a variable's values.

Measures of central tendency (mean, median, mode).

Variability in a data distribution.

Python library for data analysis with powerful data structures.

Relationship between phenomena where changes occur at similar rates.

A direct relationship where one change causes another.

Correlation does not imply causation.

Visual representation of correlations between variables.

Represents undefined or unrepresentable data in a dataset.