1. Statistical Analysis I have all this data. Now what does it mean?

2. Is your data Quantitative or Qualitative?
Continuous quantitative – measurement scale divisible into partial units
Ex-Distance in kilometers
Discrete quantitative - measurement scale with whole integers only
Ex- number of wolves born in given year
Quantitative data can be subdivided into:
Ratio - with equal divisible intervals & absolute zero
Interval - does not have absolute zero
Qualitative Nominal - objects are named or can’t be ranked
Example- Gender (male/female)
Qualitative Ordinal - objects are placed into categories that can be ranked
Example- activity of an animal on a scale of 1 to 5
Decide which type of data you have__________________

3. Describing data Central tendency (How different 2 sets of Data is)
Mode - value that occurs most often
Median - middle value when ranked highest to lowest
Mean - mathematical average
Variation (How spread out the data is)
For quantitative data –Range
For qualitative data -Frequency distribution Frequency Distribution example link

4. Statistics Software … is not going to do your job for you. It is:
not going to tell you what test to select
not going to tell you if the test you selected is the right one
not going to tell you how to interpret the test results.

5. Making decisions about descriptive statistics & Graphs
Quantitative Data
Qualitative
Parameters
Ratio data
Interval data
Nominal data
Ordinal data
Type of data
data collected using a scale with equal intervals and with an absolute zero (distance, velocity)
using a scale with equal intervals but no absolute zero (temp0C, pH)
objects are placed into categories that cannot be ranked (male/female or brown, black, red hair)
objects are placed into categories that can be ranked (Moh’s hardness scale or color ranked 1- 10)
Central tendency
Mean
Mode
Median
Variation
Range
Standard deviation
Variance
Frequency Distribution
Degrees of freedom
Total # of samples -2
(ex = 28)
(#rows –1) x (#columns-1)
Level of significance
0.025
0.05
Decide which type of data you have, parameters you will need to calculate and on your Excel chart, enter the formula for each of the parameters.

6. Inferential Statistics Is the data statistically significant?
Statistical Tests
The t-test (or Analysis of Variance):
two or more groups
to compare measurements of each group.
The Chi-square test:
counts that can be placed into yes or no categories, or categories such as quadrants.
The Pearson R Correlation:
to test how the values of one event or object relates to the values of another event or object

7. How to select statistical test
How to select statistical test? Is Dependent Variable (DV) continuous, ordinal, or nominal?

10. Null Hypothesis (μ)
…..states that there is no difference between the mean of your control group and the mean of your experimental group. Therefore any observed difference between the two sample means occurred by chance and is not significant.
If you can reject your null hypothesis then there is a significant difference between your control and experimental groups. Hence accept the alternative (original hypothesis).
Write your null hypothesis _____________________________

11. Probability - Chance Could the difference between the groups due to random chance /error?
Probability of error or p-value < 0.05 means that
the error in the research is 5/100 or below 0.05
(95% results have no error)
P<0.05
Less than 5% chance is considered to be OK.
Reject Null hypothesis
Accept your alternative (original) hypothesis
P>0.05
Greater than 5% then the data is not significant.
Must accept Null hypothesis

12. Level of significance () and Degree of freedom (df)
Level of significance () - It communicates probability of error in rejecting Null hypothesis
p-value < 0.05 means that the probability of error in the research is 5/100 (95% results with no error)
Degree of freedom (df) - It is number of independent observations in a sample.
t-test df = (n1-1) + (n2-1)
Chi-square df = (#rows – 1) (#columns – 1)
Pearson R correlation df = (n-2) subtract 2 from the number of comparisons made.
T test Chi square tables.doc

13. Accept or Reject the null hypothesis
Find the table value for the t-test and the Chi-square test
(using calculated degrees of freedom and the Level of Significance of 0.05 = 95%)
Compare calculated value to table value.
Calculated value < table value
Null hypothesis is NOT rejected
Calculated value > or = table value
Null hypothesis is rejected.