Statistics and Probability, Lecture notes of Mathematics

A branch of applied mathematics focused on analyzing, interpreting, and predicting data using techniques like data collection, hypothesis testing, and probability distributions.

Typology: Lecture notes

2025/2026

Available from 03/27/2026

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Statistics
Hypothesis Testing
Hypothesis - specific, testable prediction about the relationship between two or more variables. Often
formulated based on observations, prior knowledge, or theories. A hypothesis is usually stated in a
way that allows it to be tested through experimentation or observation.
Statement - declarative sentence that conveys information or expresses an idea. Statements can be
true or false, but they are not necessarily testable or predictive. They can be opinions, facts, or
observations without the intention of being tested.
Equality for Null Hypothesis: ≄, ≤ š‘œš‘Ÿ =
Inequality for Alternative Hypothesis: >, <, or
≠
Expressing Null and Alternative Hypothesis in Notation Form
Type of Data
Symbol
Meaning
Example
Variable
Formula
Quantitative
(numerical)
µ
Population Mean
ā— height
ā— age
ā— salary
H0:
µ
Categorical
(proportion/perc
entage)
p
Population
Proportion
ā— voters
ā— commute
rs
ā— graduates
Ha: p
Types of Errors
1. Type 1: if we reject the null hypothesis when it is true (if null and action did not align)
2. Type 2: if the null hypothesis is false and we accepted it (if null and action align)

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Statistics

Hypothesis Testing

Hypothesis - specific, testable prediction about the relationship between two or more variables. Often formulated based on observations, prior knowledge, or theories. A hypothesis is usually stated in a way that allows it to be tested through experimentation or observation. Statement - declarative sentence that conveys information or expresses an idea. Statements can be true or false, but they are not necessarily testable or predictive. They can be opinions, facts, or observations without the intention of being tested.

Equality for Null Hypothesis: ≄, ≤ š‘œš‘Ÿ = Inequality for Alternative Hypothesis: >, <, or ≠

Expressing Null and Alternative Hypothesis in Notation Form

Type of Data Symbol Meaning Example Variable

Formula

Quantitative (numerical) (^) μ

Population Mean ā— height ā— age ā— salary

H 0 : μ

Categorical (proportion/perc entage)

p

Population Proportion

ā— voters ā— commute rs ā— graduates

Ha: p

Types of Errors

  1. Type 1: if we reject the null hypothesis when it is true (if null and action did not align)
  2. Type 2: if the null hypothesis is false and we accepted it (if null and action align)