Class 1 Spring π· Flashcards
What are important applications of statistics?
Applications in various fields, including business, healthcare, and social sciences
Statistics can help in decision-making, quality control, and understanding trends.
What are meaningful applications of statistics?
Analyzing data to draw conclusions and make predictions
Meaningful applications include market research, policy formulation, and scientific research.
What are fun applications of statistics?
Fantasy Sports Analytics
Engaging in statistical analysis for games and sports can enhance enjoyment and understanding.
What are the three main components of statistics?
Collection, Analysis, Inference
These components are essential for understanding and interpreting data.
What is the significance of addressing bias in statistics?
To ensure valid and reliable conclusions are drawn from data
Bias can distort results and lead to incorrect interpretations.
What does βeverything is a distributionβ refer to in statistics?
The concept that data can be represented in terms of distributions
Understanding distributions is key to statistical analysis.
What is the difference between discrete and continuous variables?
Discrete variables are counts; continuous variables are measurements
Discrete examples: number of students; continuous examples: height, weight.
Define numerical discrete variables.
Counts of individual items or values
Examples include the number of species or days an event occurred.
Define numerical continuous variables.
Measurements of continuous or non-finite values
Examples include age, volume, and height.
What are categorical variables?
Bins or types of variables
Categorical variables can be nominal or ordinal.
Give an example of a categorical variable.
Gender
Gender is a common categorical variable used in surveys.
What are the two types of categorical variables?
Ordinal and Nominal
Ordinal variables have a defined order; nominal variables do not.
What are the 3 big lessons in statistics?
Addressing Bias, Probability Distributions, Correlation
These lessons are foundational for statistical analysis.
What does correlation indicate?
The association between two variables
Correlation does not imply causation.
What is the difference between an explanatory variable and a response variable?
Explanatory variable is independent; response variable is dependent
Understanding this relationship is crucial in regression analysis.
True or False: Correlation implies causation.
False
Correlation can exist without a causal relationship.
Fill in the blank: In statistics, a survey conducted on students can be represented in a _______.
data matrix
A data matrix organizes responses for analysis.
What is the expectation for class attendance and homework completion?
100% attendance and completion
This sets a standard for student engagement and performance.
What software is recommended for the course?
R and RStudio
These tools are commonly used for statistical analysis and data visualization.
