Summary of Aircraft Perspective presentations
Year: Aviation ENG 2
Deze samenvatting geeft alle belangrijke informatie welke in hoorcolleges gegeven
wordt.
,Table of Contents
Summary of Aircraft Perspective presentations 1
Week 01 3
Types of sampling: 3
Standard deviation 4
Difference between population and sample 4
Importing modules into Python 5
Hypothesis Testing: Methodology 6
State the hypothesis 6
Set the criteria for a decision 7
Compute the test statistic 7
Determine critical values 7
Decide 8
Population mean 8
Z-test 9
Week 02 10
Recap Sample Size & Hypothesis Testing 10
Standard error 10
T-test 11
Difference in tests: one-sample 11
Samples vs populations 11
Symbols 12
A) One-sample t-test 13
B) Paired (dependent) samples t-test 15
C) Independent samples t-test 17
Week 03 20
Recap one-sample t-tests 20
Dependent two-sample t-test 20
Assumptions for dependent two-sample t-test 20
Assumptions for independent two-sample t-test 21
Note 21
Week 04 22
Recap two-sample t-tests 22
What is linear regression? 22
Straight line equation 22
Linear regression: residuals 23
Linear regression: good residual plots 26
Linear regression: bad residual plots 26
Coefficient of determination 27
Week 06 29
Prompt Engineering 29
Automated descriptive statistics 30
Descriptive statistics/EDA 30
Recap simple linear regression 30
What is multiple regression? 30
When do you use multiple regression? 32
Multiple regression in Python 32
,Week 01
Types of sampling:
Simple random
- Each individual is chosen by chance
o Equal probability for each individual
- Chosen from population as a whole
- Unbiased sampling method
Stratified Random
- Division in groups sharing ≥ 1 characteristic
• Subgroups are called strata
- Great knowledge of population required
- Unbiased sampling method
Cluster
- Division in clusters on certain parameter
o Mostly geography-based (e.g. cities)
- n-stage cluster sampling indicates how many
subsets are still being taken after merging
- Unbiased sampling method
, Standard deviation
Population standard deviation
∑(𝑋 − 𝜇)2
𝜎=√
𝑁
Sample standard deviation
∑(𝑋 − 𝑋ˉ)2
𝑠=√
𝑛−1
Symbol definitions
Symbol Name Meaning
𝜎 Population standard deviation Spread of values in the entire population
𝑠 Sample standard deviation Spread of values in a sample
∑ Summation Add up all terms that follow
𝑋 Observation One individual data value
𝜇 Population mean True average of the population
𝑋ˉ Sample mean Average of the sample
𝑁 Population size Number of values in the population
𝑛 Sample size Number of values in the sample
Short explanation
• The population formula is used when you have all data from the population.
• The sample formula is used when you only have part of the data, so you divide
by 𝑛 − 1to avoid underestimating variability.
Difference between population and sample
Population
The population is the entire group you want to study.
Examples:
• All passengers using an airport in a year
• All aircraft inspections at a company
• All students at a university
When you have data for everyone in the group, you use the population formula.
Year: Aviation ENG 2
Deze samenvatting geeft alle belangrijke informatie welke in hoorcolleges gegeven
wordt.
,Table of Contents
Summary of Aircraft Perspective presentations 1
Week 01 3
Types of sampling: 3
Standard deviation 4
Difference between population and sample 4
Importing modules into Python 5
Hypothesis Testing: Methodology 6
State the hypothesis 6
Set the criteria for a decision 7
Compute the test statistic 7
Determine critical values 7
Decide 8
Population mean 8
Z-test 9
Week 02 10
Recap Sample Size & Hypothesis Testing 10
Standard error 10
T-test 11
Difference in tests: one-sample 11
Samples vs populations 11
Symbols 12
A) One-sample t-test 13
B) Paired (dependent) samples t-test 15
C) Independent samples t-test 17
Week 03 20
Recap one-sample t-tests 20
Dependent two-sample t-test 20
Assumptions for dependent two-sample t-test 20
Assumptions for independent two-sample t-test 21
Note 21
Week 04 22
Recap two-sample t-tests 22
What is linear regression? 22
Straight line equation 22
Linear regression: residuals 23
Linear regression: good residual plots 26
Linear regression: bad residual plots 26
Coefficient of determination 27
Week 06 29
Prompt Engineering 29
Automated descriptive statistics 30
Descriptive statistics/EDA 30
Recap simple linear regression 30
What is multiple regression? 30
When do you use multiple regression? 32
Multiple regression in Python 32
,Week 01
Types of sampling:
Simple random
- Each individual is chosen by chance
o Equal probability for each individual
- Chosen from population as a whole
- Unbiased sampling method
Stratified Random
- Division in groups sharing ≥ 1 characteristic
• Subgroups are called strata
- Great knowledge of population required
- Unbiased sampling method
Cluster
- Division in clusters on certain parameter
o Mostly geography-based (e.g. cities)
- n-stage cluster sampling indicates how many
subsets are still being taken after merging
- Unbiased sampling method
, Standard deviation
Population standard deviation
∑(𝑋 − 𝜇)2
𝜎=√
𝑁
Sample standard deviation
∑(𝑋 − 𝑋ˉ)2
𝑠=√
𝑛−1
Symbol definitions
Symbol Name Meaning
𝜎 Population standard deviation Spread of values in the entire population
𝑠 Sample standard deviation Spread of values in a sample
∑ Summation Add up all terms that follow
𝑋 Observation One individual data value
𝜇 Population mean True average of the population
𝑋ˉ Sample mean Average of the sample
𝑁 Population size Number of values in the population
𝑛 Sample size Number of values in the sample
Short explanation
• The population formula is used when you have all data from the population.
• The sample formula is used when you only have part of the data, so you divide
by 𝑛 − 1to avoid underestimating variability.
Difference between population and sample
Population
The population is the entire group you want to study.
Examples:
• All passengers using an airport in a year
• All aircraft inspections at a company
• All students at a university
When you have data for everyone in the group, you use the population formula.
