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Science Unit 3 - Coggle Diagram
Science Unit 3
Variables
Independent Variables:
The Independent Variable is the thing you CHANGE on purpose within an experiment
Ask yourself: What am I testing?
Dependent Variables:
The Dependent Variable is the thing you measure to see the effect of the Independent Variable
Ask yourself: What changes because of my Independent Variable?
Control Variable:
The Control Variable is the baseline that we COMPARE OUR RESULTS TO
There is usually 1 control variable
Constants:
Constants are everything we keep the same within an experiment
Ask yourself: What factors could mess up my experiment if they were changed?
Things we Calculate
Standard Deviation:
Standard Deviation is a number that tells you how spread out your data is.
A Small SD = data points are close to the mean
A Large SD = data points are far from the mean
We calculate SD by:
1) Find the Mean of the data
2) Subtract the mean from each data point to get the difference
3) Square each difference
4) Find the mean of these square differences - this is the variance
5) Take the square root of the variance - this is your SD
P-Value:
If the P-Value is over 0.05, we accept the Null Hypothesis.
If the P-Value is less than or equal to 0.05, we reject the Null Hypothesis (and accept the Alternative Hypothesis)
Feedback Loops
Negative Feedback Loops:
Negative Feedback Loops are where the body responds to reverse a change and bring conditions back to normal
The purpose is to maintain homeostasis
It counteracts the change
Positive Feedback Loops:
Positive Feedback Loops are where the body responds to amplify a change, moving conditions further away from normal
Usually for temporary processes
Amplifies the change
T-Tests
What are T-Tests?
Paired T-Test:
When you're testing the same group of people, in a before and after situation, this is a paired T-Test.
Pairs of people, same population.
An example would be measuring a group of individuals heartrate, then placing them in a freezer, and then measuring their heartrate again.
Unpaired T-Test
When you're testing different people and different organisms, this is an unpaired T-Test.
An example would be placing one group of people in a freezer and one group stays out of the freezer - different populations.
If you have the variants, the two samples are getting two variances, because not all peoples heartrates are going to be the same
Equal variances happen when when the variance is about the same
If the variance is different (their are large variances in our hearrates but the Canadians are very similar) then we use unequal variants
P-Value:
If it is less than 0.5, it supports the ALTERNATE HYPOTHESIS
If it is greater than or equal to 0.5, it supports the NULL HYPOTHESIS
The job of a T-Test is to tell you whether this set of data is statistically significantly different than this other set of data
Tails
If you have a hypothesis which tells you which direction things will change, USE 1 TAIL
If you have no idea which direction the thing might change, USE 2 TAILS