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Introduction to Statistics Concepts
Jan 29, 2025
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Statistics Lecture Notes
Definition of Statistics
Statistics: The collection and interpretation of data.
Used to measure and analyze variability (heights, weights, hair color, etc.).
Types of Statistics
Inferential Statistics
Involves analyzing a sample to make judgments about a population.
Descriptive Statistics
Involves summarizing data and describing it (e.g., average midterm score).
Tools: Histograms, graphs.
Course Structure
First part: Descriptive statistics.
Second part: Inferential statistics.
Basic Definitions
Population
: Total amount of items (people, cats, vehicles).
Sample
: A small part of the population used for study.
Sample Size
: The number of items in a sample.
Variables
Variable
: Characteristic of what is being studied (measurable, countable, categorizable).
Examples: Height, weight, hair color.
Types of Variables
:
Quantitative Variables
Measured in numbers, suitable for arithmetic calculations (e.g., average).
Examples: Height, weight, midterm score.
Categorical Variables
Values that place things into groups or categories.
Examples: Hair color, type of cat, letter grade.
Types of Categorical Variables
Ordinal
Logical ordering of values (e.g., letter grades).
Nominal
No logical ordering (e.g., hair color).
Types of Quantitative Variables
Discrete Variables
Measurable in certain numbers (e.g., number of pets).
Continuous Variables
Can take any numerical value (e.g., weight).
Recap
Population
: Total number of items.
Sample
: Part of the population examined.
Sample Size
: Number in a sample.
Variable of Interest
: What is measured from each individual.
Data Types
:
Quantitative (e.g., midterm scores)
Categorical (e.g., letter grades)
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