Python Fundamentals Quiz: 99 Essential Concepts
Section 1: Basics, Variables, and Data Types (Q1–Q16)
Q1 Who created Python? Yeongin Kim / Bill Gates / Justin Martin / Guido Van Rossum
Q2 What does the Garbage Collector do? Hides memory / Deletes object permanently, frees memory / Renames object / Creates new object
Q3 What type of language is Python? Compiled / Dismissed / Interpreted / Associated
Q4 A Syntax Error occurs when misusing: Keywords / Parenthesis / Punctuations / One of the above
Q5 A Logical Error results in: Unexpected output / Crash
Read MoreStatistical Forecasting Methods and Time Series Analysis
Regression Analysis: Modeling Relationships
Regression analysis is a statistical technique used to model and analyze the relationship between a dependent variable (outcome) and one or more independent variables (predictors). It helps in:
- Understanding relationships between variables.
- Making predictions based on past data.
- Identifying key factors influencing an outcome.
Types of Regression
A. Linear Regression
Linear Regression models a relationship between the dependent variable (Y) and independent variable(
Read MoreEssential Statistical Concepts: Data Analysis and Modeling
Statistics: techniques (collecting,organizing,analysing,interpreting data)
Data may be:
quantitative (values expressed numerically) qualitative: (characteristics being tabulated). Descriptive statistics
: techniques summarize, describe numerical data= easier interpretation – can be graphical/involve computational analysis. Inferential statistics: techniques about decisions about statistical population/process are made based only on a sample being observed – use of probability concepts. VARIABLES:
Time Series Analysis and Regression Modeling in R
R Setup and Initial Data Handling
Setting the working directory:
setwd("/Users/hajdumarcell/Downloads/Öko. II. R Jegyzet")Data inspection and preparation:
str(Titanic)
PS4$Date <- as.Date(PS4$Date)Basic visualization using ggplot2:
ggplot(PS4, aes(x=Date, y=Google_PS4)) + geom_line()Regression Modeling with Dummy Variables
The general regression model structure, including trend ($t$) and quarterly dummy variables ($DQ$):
$$Y_t = \beta_0 + \beta_1 \times t + \beta_2 \times DQ_1 + \beta_3 \times DQ_
Read MoreResearch Sampling Methods: Probability vs. Non-Probability Techniques
Probability and Non-Probability Sampling Methods
Probability (Random) Sampling
Probability sampling, also known as random sampling, is a method where the probability of being selected is known, meaning every member of the wider population has an equal chance to be included. The primary aim is for generalizability and wide representation.
Purpose and Example
- Purpose: To select a group of subjects representative of the larger population from which they are selected.
- Example: A university randomly selects
Essential Statistical Concepts and Formulas Reference
Descriptive Measures: Center and Variability
Measures of Variation
- Standard Deviation (SD): The average measure of distance between data points and the mean (the square root of the variance). It indicates how far the data is, on average, from the mean.
- Calculation: Find the variance and take its square root.
- Coefficient of Variation (CV): Used to compare the standard deviation of two different data sets. Shown as a percentage, it measures variation relative to the mean.
- Formula: CV = (Standard Deviation