Summer Work Review

Question 1

What is an observation?

Answer 1

A feature of a sysem that you know to be true because you can see it immediately without testing it

Question 2

What is an assumption?

Answer 2

A feature of a system that you assume to be true but that you don’t/can’t test it right away.

Question 3

What is a hypothesis

Answer 3

A proposed answer to a scientific question

Question 4

What is a regular hypothesis also known as?

Answer 4

An alternative hypothesis

Question 5

What is a null hypothesis?

Answer 5

A proposition that an observed difference or correlation between two samples could be purely incidental. Nothing is caused by anything else

Question 6

Experimental Design

Answer 6

The way that your experiment is set up. Your hypothesis, predictions, experiment design.
(independent variable - the variable that you change
dependent variable - the variable that changes because of the independent variable
Trials - how many will you have? it should be more than one.
control groups - group where everything will stay the same)

Question 7

Why do we use models?

Answer 7

We may not be able to directly observe something it’s full scale due to its size or because we can’t test certain things on a real world system

Question 8

Open System

Answer 8

Exchanges everything with the world around it like energy and matter (e.g An ecosystem or a national park)

Question 9

Closed System

Answer 9

Exchanges only energy with its surroundings (e.g. Earth)

Question 10

Isolated System

Answer 10

Exchanges almost nothing with its surroundings (this is usually considered to be theoretical)

Question 11

What is negative feedback?

Answer 11

counteracts a change in equilibrium to make something normal (e.g. your pulse rate drops after exercising)

Question 12

What is positive feedback?

Answer 12

invokes a change in a system that will take it out of equilibrium (e.g. childbirth or your pulse rate going up after exercising)

Question 13

Accuracy

Answer 13

How close measurements are to the true or ideal value. Measurements could be all relatively accurate but not close to each other.

Question 14

Precision

Answer 14

How close repeated measurements are to each other

Question 15

Quantitative Data

Answer 15

Data that you can count or measure

Question 16

Discrete Data

Answer 16

Data that doesn’t really have a range and can’t be split up. the Data points somewhat skip around (e.g. integer data like number of children)

Question 17

Continuous Data

Answer 17

Data that is in more of a range and can be a part of a number(e.g. decimal data such as height)

Question 18

Qualitative Data

Answer 18

Non-numerical data

Question 19

Ranked Data

Answer 19

Data that has a specific order

Question 20

Rate

Answer 20

Demonstrates how a variable changes over time

Question 21

Probability

Answer 21

how likely something is to happen

Question 22

Percentages & Fractions

Answer 22

Fraction demonstrates how many parts of a whole are present. Percentages are fractions taken out of 100

Question 23

Ratio

Answer 23

Give a relative amount of two or more qualities

Question 24

Logs

Answer 24

transforms data to make it easier to work with.

Question 25

Exponential growth

Answer 25

When a value grows at a rapidly increasing rate. A graph that demonstrates exponential growth will often resemble a “J” (used to demonstrate population growth)

Question 26

REMINDER. NOT A QUESTION

Answer 26

Be familiar with the concept of Surface Area and Volume. You don’t need to memorize the equations.

Question 27

Percent Error Definition

Answer 27

Measures how far an experimental value is from an ideal value using percentage

Question 28

What is the equation for Percent Error?

Answer 28

((experimental - ideal value)/(ideal value)) * 100

Question 29

Line Graphs

Answer 29

Plot points on a graph and then connect the dots. Usually used when one variable affects another

Question 30

Scatter Graphs

Answer 30

Plot the points and then draw a line of best fit through the points. Data is continuous for both variables. Often, there is no dependent variable, but the two variables are correlated

Question 31

Histograms

Answer 31

Continuous Data demonstrated. Like a bar graph, but the bats are touching. Often used to represent frequency

Question 32

Bar Graphs

Answer 32

Used for discontinuous/discrete data. There are no dependent or independent variables.

Question 33

Correlation Vs. Causation

Answer 33

Just because two things are correlated does not mean one caused another.

Question 34

Mean

Answer 34

The average
Rules:
1. Don’t take the average of two averages
2. Don’t calculate the mean of ratios
3. Don’t take the mean of a measurement that isn’t linear (e.g. PH)

Question 35

Median

Answer 35

The middle number

Question 36

Mode

Answer 36

The number that appears the most

Question 37

Range

Answer 37

Highest to lowest value

Question 38

Standard Deviation

Answer 38

putting a number to the variability of data. Demonstrated how far it is from the mean.

Question 39

Why is Random Sampling important?

Answer 39

To eliminate bias within your experiment.

Question 40

Why is it important to have a large sample size?

Answer 40

The more samples you use, the more accurate your results will become.