1. Discussion Discuss your results.
Whether or not the results answered your research questions
Compare your results with the literature: agree or doe not agree and why
Not agreeing with the literature could be due to the limitations or the experimental/study design.
What recommendations can be made to improve or reduce deficiencies. (I.E. evaluating the ventilation system)

2. Discussion Correlation outcomes?
I.E. Training effectiveness (Y-N) and familiarity with the SDS (Y-N): phi correlation and chi square test.
- Interpretation:
Significant/Strong correlation  training is effective.
Not significant  Training is not effective and should be updated and modified.

3. Conclusions Summary of the major findings and recommendations.
References
Appendices: supporting document (cover letter, survey, calculations, policy, procedure, consent form, etc.)
Make sure to
When writing you final project make sure to change the tense from future to past, since everything has been done.
APA style, cover letter, table of content.

4. Measures of Relative Position
Z Score
A standard score (z score) is a measure of relative position which is appropriate when the test data represent an interval or ratio scale of measurement. The z score is the position of value in terms of the number of standard deviations that a value is from the mean.
A typical z score is between 3 and -3, therefore z scores larger than +3 or -3 would probably be associated as an outlier =

5. Student # 1 has the higher score
Example of z score:
Student 1 GPA of 3.45 on a 4.0 scale
Student 2 GPA of 3.9 on a 5.0 scale
Which student has the higher GPA?
What else do you need?
#1 x = 2.5 & SD = 1.8
#2 x = 3.2 & SD = 2
Student # 1 has the higher score
Student 1 Z =
= .53
1.8
Student 2 Z =
=.35
2.0

6. Z scores and Percentages of the Population
Using z scores and a z table, one can determine the percentages of populations expected to score above and below the obtained z score. All z scores to the right of the mean are positive while all z scores to the left of the mean are negative. The z table values range from to

11. Z score
For example, to locate a z score of , go to the first column and locate - 3.4
The digit located in second decimal place is a 5 so go across to the column labeled .05
So what is the value  Use the Z Table

12. Z score
Answer:
The number in the table that is in Row and under column .05 is Multiplying this number by 100 indicates that .03% of the population is expected to lie between the z score of and the tail end of the curve.

13. Z score – Example 2:
What is the probability that an individual picked randomly will have an IQ score between 100 and 115?
Additional Information needed:
IQ's are normally distributed with a mean of 100 and a standard deviation of 10.
Refer to a "Z Score" table to find the percentage of the population.
P (100 < x < 115) = ?

14. P (100 < x < 115) =. P ((100-100)/10 < z < (115-100)/10) =
P (100 < x < 115) = ? P (( )/10 < z < ( )/10) = ? P (0 < z < 1.5) = ?

15. = – 0.50 =

16. T test and ANOVA
The t-test and ANOVA examine whether group means differ from one another. The t-test compares two groups, while ANOVA can do more than two groups.
The t-test and ANOVA have three assumptions: independence assumption (the elements of one sample are not related to those of the other sample), normality assumption (samples are randomly drawn from the normally distributed populations with unknown population means; otherwise the means are no longer best measures of central tendency, thus test will not be valid), and equal variance assumption (the population variances of the two groups are equal)