Here is my example of conducting a T Test with the given data on Gender and Millennial Age Score.
Below is the completed charts from the activity that Dr. Pierce asked us to do.
With the bottom two charts, Dr. Pierce asked us what about the impact bewteen Chrome and IE on Scores? This indicates that these two had the least impact on scores!
So back to my original research questions, hypothesis, and null hypothesis:
Research Questions:
1. Why do the Males have more discussion postings than females?
2. Why do the Females have less discussion postings than males?
1. Why do the Males have more discussion postings than females?
2. Why do the Females have less discussion postings than males?
Hypothesis:
1. Males have more discussion postings due to their lower Millennial Age Score.
2. Females have less discussion postings due to their higher Millennial Age Score.
2. Females have less discussion postings due to their higher Millennial Age Score.
Null Hypothesis: There is no difference between male and female and discussion postings.
Independent Variables: Gender (sex)
Dependent Variables: Discussion Postings and Millennial Age Score.
Millennial Information:
Within the Femalse 14/22 are to be considered Millennial due to being 73 or higher = 63.63%.
Within the Male 3/7 are considered Millennial due to being 73 or higher = 42.85%.
Discussion Postings:
The first thing that I did was run the Desriptive Data on just Discussion Postings alone. That helped me to determine that the Median was 15. So from that I formulated that those who had 14 or less discussion postings should have Millennial scores higher than 73. In saying that those who had 15 or more discussion postings should have a Millennial score less than 73. I broke the data first into males and females due to my Hypothesis. This theory held true to 1/3 males in the 1-14 discussion postings range and 2/4 in tge 15- and up discussion postings range. This creates a combined figure of 3/7=42.85% accuracy. I then examined the females; for 8/11 females this theory was accurate in the 1-14 discussion postings category. 5/11 were true in the 15 and higher discussion posting category. These combine for 13/22 accuracy in my hypothesis which falls at a 59%.
I feel that my hypothesis seems to be more accurate with the Females than the Males due to my calculations. So do Females have less discussion postings because of their Millennial Age Score? Sure 59% of them do. Do Males have more discussion postings due to their lower Millennial Age Score? For 42.85% this is true.
In regards to my Null Hypothesis I feel as if it seems to still be valid. This can stand its ground due to the fact that there is a difference between males and female for discussion postings.
This entire activity is a total reflection of standard # 5. T Tests are a useful way to demonstrate data in a manor that reflects students progress and self reflection on the teacher. This is useful in how we may change our instruction, see our areas of weakness, and make connections of why students are where they are. (In positive and negative ways) This allows a teacher to see the students strengths and weaknesses. This allows insight for the teacher to determine what to do about the weaknessess and turn them into strengths. By using a T Test we are not just looking at one variable we are able to use multiple variables in which allows us to dig deeper and become more precise in the accurate use of data.
This activity was the most difficult and most time consuming of them all! There were nights of tears and tons of frustration!!