Essential Statistical Concepts for Data Analysis
Fundamentals of Business Statistics
Statistics Definition
The field concerning the collection, analysis, interpretation, and presentation of data used for the decision-making process in the business area.
Descriptive Statistics
Involves data collection methods, description, and summary data visualization. Focuses on the data as they are.
Inferential Statistics
The generation of models, inferences, and predictions associated with the phenomenon in question (predicting how the variable will behave).
Populations
Read MoreKey Statistical Concepts: Non-Parametric Tests and Time Series Analysis
Non-Parametric Methods
Non-parametric methods are statistical tests that do not assume the data follows a specific distribution, such as the normal distribution. They are often used when the assumptions of parametric tests are violated.
- Mann-Whitney U Test (Wilcoxon Rank-Sum Test): Used to compare the distributions of two independent groups or samples to determine if they have different medians. It is an alternative to the independent samples t-test.
- Wilcoxon Signed-Rank Test: Used to compare the medians
Statistical Fundamentals and Key Concepts Reference
Hypothesis Testing and P-Values
P-Value Definition
The p-value is the probability of observing a statistic as extreme (or more extreme) as the sample statistic, assuming the null hypothesis (H₀) is true.
Interpretation
- Large p-value: Evidence in favor of H₀ (Null Hypothesis).
- Small p-value: Evidence in favor of Hₐ (Alternative Hypothesis).
Types of Errors
- Type I Error (α): Rejecting H₀ when H₀ is true.
- Type II Error (β): Failing to reject H₀ when H₀ is false.
Study Design Fundamentals
- Sample:
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: