問題一覧
1
A linear line that tries to approximate the relationship between two variables by getting near as many data points as possible
2
A line of best fit that minimises the sum of the squares of the distances of each data point from the line
3
y = a + bx, where a and b are constants
4
a is the intercept (y value at x = 0), b is the gradient (change in y for a change in x of 1)
5
The data is positively correlated
6
The data is negatively correlated
7
When there is a linear relationship between two variables
8
When the value for the dependent variable is within the given range of data
9
Predicting values within the given range of data
10
Predicting Values outside the given range of data
All Maths Notation
All Maths Notation
Oluwole Akande · 72問 · 2年前All Maths Notation
All Maths Notation
72問 • 2年前Financial Ratio Analysis - Liquidity Ratios and Gearing
Financial Ratio Analysis - Liquidity Ratios and Gearing
Oluwole Akande · 9問 · 3年前Financial Ratio Analysis - Liquidity Ratios and Gearing
Financial Ratio Analysis - Liquidity Ratios and Gearing
9問 • 3年前Topic 6 - Further Mechanics - Glossary
Topic 6 - Further Mechanics - Glossary
Oluwole Akande · 8問 · 2年前Topic 6 - Further Mechanics - Glossary
Topic 6 - Further Mechanics - Glossary
8問 • 2年前Command Words
Command Words
Oluwole Akande · 26問 · 2年前Command Words
Command Words
26問 • 2年前Circuit Symbols
Circuit Symbols
Oluwole Akande · 15問 · 2年前Circuit Symbols
Circuit Symbols
15問 • 2年前Topic 4 - Materials - Upthrust and Viscosity
Topic 4 - Materials - Upthrust and Viscosity
Oluwole Akande · 5問 · 2年前Topic 4 - Materials - Upthrust and Viscosity
Topic 4 - Materials - Upthrust and Viscosity
5問 • 2年前Topic 5 - Waves and Particle Nature of Light - Ray Diagrams
Topic 5 - Waves and Particle Nature of Light - Ray Diagrams
Oluwole Akande · 5問 · 2年前Topic 5 - Waves and Particle Nature of Light - Ray Diagrams
Topic 5 - Waves and Particle Nature of Light - Ray Diagrams
5問 • 2年前Topic 8 - Nuclear and Particle Physics - Linear Accelerator and Particle Detectors
Topic 8 - Nuclear and Particle Physics - Linear Accelerator and Particle Detectors
Oluwole Akande · 14問 · 2年前Topic 8 - Nuclear and Particle Physics - Linear Accelerator and Particle Detectors
Topic 8 - Nuclear and Particle Physics - Linear Accelerator and Particle Detectors
14問 • 2年前Topic 10 - Space - Trigonometric Parallax
Topic 10 - Space - Trigonometric Parallax
Oluwole Akande · 8問 · 2年前Topic 10 - Space - Trigonometric Parallax
Topic 10 - Space - Trigonometric Parallax
8問 • 2年前Topic 7 - Electric and Magnetic Fields - Glossary
Topic 7 - Electric and Magnetic Fields - Glossary
Oluwole Akande · 7問 · 2年前Topic 7 - Electric and Magnetic Fields - Glossary
Topic 7 - Electric and Magnetic Fields - Glossary
7問 • 2年前Chapter 7 - Electric and Magnetic Fields - Coulomb's Law
Chapter 7 - Electric and Magnetic Fields - Coulomb's Law
Oluwole Akande · 7問 · 2年前Chapter 7 - Electric and Magnetic Fields - Coulomb's Law
Chapter 7 - Electric and Magnetic Fields - Coulomb's Law
7問 • 2年前Chapter 7 - Electric and Magnetic Fields - Electric Field Strength
Chapter 7 - Electric and Magnetic Fields - Electric Field Strength
Oluwole Akande · 11問 · 2年前Chapter 7 - Electric and Magnetic Fields - Electric Field Strength
Chapter 7 - Electric and Magnetic Fields - Electric Field Strength
11問 • 2年前Chapter 7 - Electric and Magnetic Fields - Electric Potential
Chapter 7 - Electric and Magnetic Fields - Electric Potential
Oluwole Akande · 12問 · 2年前Chapter 7 - Electric and Magnetic Fields - Electric Potential
Chapter 7 - Electric and Magnetic Fields - Electric Potential
12問 • 2年前Chapter 7 - Electric and Magnetic Fields - Capacitor Discharge
Chapter 7 - Electric and Magnetic Fields - Capacitor Discharge
Oluwole Akande · 11問 · 2年前Chapter 7 - Electric and Magnetic Fields - Capacitor Discharge
Chapter 7 - Electric and Magnetic Fields - Capacitor Discharge
11問 • 2年前問題一覧
1
A linear line that tries to approximate the relationship between two variables by getting near as many data points as possible
2
A line of best fit that minimises the sum of the squares of the distances of each data point from the line
3
y = a + bx, where a and b are constants
4
a is the intercept (y value at x = 0), b is the gradient (change in y for a change in x of 1)
5
The data is positively correlated
6
The data is negatively correlated
7
When there is a linear relationship between two variables
8
When the value for the dependent variable is within the given range of data
9
Predicting values within the given range of data
10
Predicting Values outside the given range of data