1. 1.1 Statistical Analysis

2. 1.1.1 State that error bars are a graphical representation of the variability of data
all measurements are subject to error so it is important to show this by using error bars
error bars can be used for both variables (x and y axis)
csupomona.edu

3. 1.1.2 Calculate the mean and standard deviation of a set of values
When analyzing data, it is important to know both the means and the standard deviation
mean formula
mean A. colubris –
15.9
mean C. Latirostris –
18.8

4. 1.1.2 Calculate the mean and standard deviation of a set of values
Standard deviation formula

5. 1.1.3 State that the term standard deviation is used to summarize the spread of values around the mean, and that 68% of the values fall within one standard deviation of the mean.
Approximately 2/3 (68%) of the data falls within one SD
95% of the data falls within two SD

6. 1.1.4 Explain how the standard deviation is useful for comparing the means and the spread of data between two or more samples
A small value of standard deviation indicates that the data is not spread, and very close to the mean value (more reliable)
A large value indicates a wider spread of data (perhaps, less reliable)

7. 1.1.5 Deduce the significance of the difference between two sets of data using calculated values for the t and the appropriate tables
We use a t-test to see if there is a significant (real) difference between to samples or two sets of data
In other words, “Are the means far enough apart to call them truly different ?”

8. 1.1.5 Deduce the significance of the difference between two sets of data using calculated values for the t and the appropriate tables
With a t-test we always start with the Null Hypothesis (Ho) – “There is no significant difference between results”
P ranges from 0 (not likely) to 1 (certain)
Normally, in biology, we use 0.05 (means 95% certainty) to determine our critical value.
If our t value is more than the critical value (cv), then our null hypothesis is rejected
t>cv – null hypothesis rejected
t<cv – null hypothesis accepted
Degrees of freedom (df) = (the total sample size) - 2

9. 1.1.5 Deduce the significance of the difference between two sets of data using calculated values for the t and the appropriate tables
2.09
t (3.65) > cv (2.09)
So….There is a significant difference between the heart rates of swimmers and non-swimmers

10. 1.1.5 Deduce the significance of the difference between two sets of data using calculated values for the t and the appropriate tables
(Ho) – There is no significant difference in the bill length between the two birds
Excel can determine the P value directly. We don’t need the table for critical values
Calculated value for P
Much less than the value for p we use for biology = 0.05
If P<p, then we reject (Ho)
The (Ho) is rejected – therefore there is a significant difference in bill length.

11. 1.1.6 Explain that the existence of a correlation does not establish that there is a causal relationship between two variables

12. 1.1.6 Explain that the existence of a correlation does not establish that there is a causal relationship between two variables
When making graphs, use a line graph if the independent variable is under control of the student who is performing the experiment/investigation
Positive correlation – as CO2 concentration increases, the rate of photosynthesis increases
Negative correlation – as college students consume more drinks their GPA decreases
Be careful. A correlation does not always mean there is a relationship.
Since 1995, the rate at which the polar ice caps melt has increased.
Also, I have been getting more gray hair.
Therefore, the more gray hair I get, the faster the polar ice caps melt.”

13. 1.1.6 Explain that the existence of a correlation does not establish that there is a causal relationship between two variables