1. For example, lets say a farmer from Jolly Fun Farms was trying to see you fertilizer that
he used for his crops.
2. The farmer is stating that this fertilizer is the best around and you will only grow
beautiful crops by only using this fertilizer.
3. The farmer proposes a play that he will show you that his fertilizer is the best.
1. Being the consumer, you are a bit skeptic of this farmer and what he is telling you.
2. At the end result, you and the farmer came up with the idea that you two will use Sad
Suffering Farm as your soil to plant.
3. You then will section off the soil into even sections and use the fertilizer in every
II. MEASURING RELATIONSHIPS
A. Differences Between Groups
1. One group is the “T” group, which tests hypothesis with only 2 groups.
2. The ANOVA group tests the relations between 3 groups.
B. Relationships Between Variables
1. The correlation (r), variable in the results with 2 tested groups.
2. Regression is the variable in results with 3 tested groups.
C. Universal Points & Null
1. Universal points measure the variables in only the sample that was being tested.
2. Null is the term that is used when “assumption is no relationship exists in population”.
3. Just like scientists, the NULL is very skeptic. NULL never thinks the hypothesis will be
4. “P” is the value that measures the evidence for NULL.
5. If “P” is small, (P< .05), we reject the NULL statement.
6. Our default assumption is always wrong.
7. The bigger the samples are, the easier it is to get an accurate result.
III. STRENGTH AND DIRECTION
A. Correlation, Regression Reflect Both Strength and Direction
1. It is easy to get accurate results when you use the “T” and ANOVA tests.
2. In class, the tests/theories we discuss deals with people.
3. Since we are dealing with “flawed, different” sample, (people), the correlation we will
always see is “R=.03”
4. This correlation has a very slight negative slope. 9-5-13
IV. DIFFERENT WAYS TO TEST
A. Content Analysis
1. This way of testing uses two sample groups.