1. Introduction to statistics August 19, 2014
Pick up your science journal at the front.
Hold onto your IA fruit ripening comments.

2. Essential Questions What is scientific inquiry?
How do we define results to be significant?

4. The Vitruvian Man
Ideal human proportions described by Roman architect Vitruvius
the length of the outspread arms is equal to the height of a man
from below the chin to the top of the head is one-eighth of the height of a man
from above the chest to the hairline is one-seventh of the height of a man.
the maximum width of the shoulders is a quarter of the height of a man.
the distance from the elbow to the armpit is one-eighth of the height of a man.
the length of the hand is one-tenth of the height of a man.
the foot is one-seventh of the height of a man.
from below the foot to below the knee is a quarter of the height of a man.
from below the knee to the root of the penis is a quarter of the height of a man.
The drawing is based on the correlations of ideal human proportions with geometry described by the ancient Roman architect Vitruvius in Book III of his treatise De Architectura. Vitruvius described the human figure as being the principal source of proportion among the Classical orders of architecture. Vitruvius determined that the ideal body should be eight heads high. Leonardo's drawing is traditionally named in honor of the architect.

5. Pick up your science journal at the front.
Statistics August 21, 2014
Pick up your science journal at the front.

6. CONTINUOUS?
DISCRETE?

7. Standard deviation
Used to summarize the spread of values around the mean
68% of the values fall within one standard deviation of the mean.

8. Standard deviation
A small standard deviation indicates that the data is clustered closely around the mean value
A large standard deviation indicates a wider spread around the mean

9. Error bars
Error bars are graphical representation of the variability of data (standard deviation)

10. T-test
Used to determine whether there is a significant difference between means of two populations
Examples:
Compare the size of beak for two kinds of finches
Compare the heart rate before/after drinking coffee
When is it ‘significant’?
There is a significant difference when the difference is caused by a factor other than chance
To use a t-test, samples must be greater than 10

11. When can we say that something is significant?
P = probability that the difference is due to chance
If P < 0.05 (or 5%)
The probability that the two groups is different is due to less than 5% chance
95% due to ‘something other than chance’ = 95% confidence level
There is a significant difference between two groups
If P > 0.05
The probability that the two groups is different is due to greater than than 5% chance
Less than 95% due to ‘something other than chance’ = 95% confidence level
There is no significant difference between two groups

12. How do we know when results support a conclusion?
Statistics t-test
How do we know when results support a conclusion?
TODAY:
In your blog: What is the significance of the t-test? What is the p-value?
This week’s feedback distributer: Silvana
ANNOUCEMENT:
Quiz
Lab due date

13. T-test
Used to determine whether there is a significant difference between means of two populations
Sample size of at least 10 required

14. Instructions (1) Command terms quiz
Finish first t-test sheet and show me.
Go on to the second t-test packet.
Begin to work on your lab (ONLY DCP & CE). For your DCP, include: all calculations (means, SD, t-test) and graphs you created. Follow the IA guidelines VERY carefully on formatting of the data.

15. How do we know when results support a conclusion?
Statistics t-test
How do we know when results support a conclusion?
TODAY:
In your blog: What is a correlation? How is it different from causation?
This week’s feedback distributer: Silvana
ANNOUCEMENT:

16. Correlation suggests relationships between two sets of data
Some causal relationships
Temperature vs enzyme activity
Concentration vs rate of diffusion
CO2 concentration vs rate of photosynthesis
Need to have carefully controlled variables

17. Examples of correlation

18. Correlation equals causation?

20. Instructions Finish t-test packet. SHOW me when you are done!
Begin to work on your lab (ONLY DCP & CE). For your DCP, include: all calculations (means, SD, t-test) and graphs you created. Follow the IA guidelines VERY carefully on formatting of the data. Make a star by the sections you don’t understand in the rubric/IA guide and ask me questions.