VL 1 Flashcards
What is a scalar?
a scalar refers to a single numerical value that represents a measurement or quantity without any associated direction. e.g: x=6
What is a vector?
a vector refers to a collection of multiple values or measurements arranged in a specific order, often representing a set of variables or observations.
e.g: c(2,3,6,8,9,11) Body height in cm
What is an Array?
an array refers to a multidimensional data structure that stores a collection of values organized in a rectangular grid, often used to represent datasets with multiple variables or dimensions.
What’s a Matrix?
a matrix refers to a two-dimensional array of numbers arranged in rows and columns, commonly used to represent relationships between variables or to store tabular data.
Matrix has its own commands in R.
What does Matrix, Array and Vector have in common?
Matrices, arrays, and vectors are all multidimensional data structures that store homogeneous elements, support indexing, and are commonly used in mathematical operations and data analysis.
What is a List?
a list refers to a data structure that can contain elements of different types, such as vectors, matrices, arrays, or other lists, allowing for flexible organization and storage of heterogeneous data. Lists provide a convenient way to represent and manipulate complex data structures in statistical analysis, modeling, and programming.
(a list is like a container that can hold different types of data, such as numbers, texts, or other lists. It allows you to store and organize various pieces of information together, making it useful for handling different types of data in a flexible and organized manner during statistical analysis)
What’s a Data frame?
A data frame in statistics is a two-dimensional data structure that represents tabular data, similar to a spreadsheet or a database table. It is composed of rows and columns, where each column can contain data of a different type (numeric, character, factor, etc.), and each row represents a unique observation or case. Data frames are commonly used for organizing and analyzing structured data in statistical analysis and data manipulation tasks.
Explain similarities and differences between R commands data, read.table, source and load
ALTKLAUSURFRAGE
Similarities:
All four commands are used for data handling and loading in R.
They allow for accessing, manipulating, or loading data into the R environment.
They play a role in data analysis and programming tasks in R.
Differences:
- data() is specifically used to load built-in datasets in R by their names.
- read.table() is employed for reading data from external text files and creating a data frame.
- source() executes R code stored in external files, often used for loading functions or scripts.
- load() loads previously saved R objects, such as data frames or models, into the R environment.
Explain briefly the aims of inferential and descriptive statistics.
ALTKLAUSURFRAGE
Descriptive Statistics:
Descriptive statistics aims to describe and summarize the main characteristics of a dataset. It helps to understand the data by providing measures like averages, ranges, and graphs that give us a clear picture of what the data looks like.
Inferential Statistics:
Inferential statistics aims to make predictions and draw conclusions about a larger group based on a smaller sample. It uses probability and statistical techniques to analyze the sample data and make inferences about the population as a whole.
In summary, descriptive statistics focuses on summarizing and describing data, while inferential statistics aims to draw conclusions and make predictions about populations based on sample data.
