Like this:

Sorry Mara but i’m taking over your post. If Rebecca is reading this, can ya do  me a favor and make me an admin on this blog. Apparently i can only edit on this one, and i can’t post on my old groups. Must’ve gotten angry when i got switched around.

Anyway! Here’s our graphs so far.

1) A random event is impossible to predict and occurs without preference over other events.  Random events interfer with our ability to predict the future because their occurence does not follow a pattern.   A systematic event is one that creates a bias. Systematic events are not random, but can also interfere with the integrity of data.  As statisticians we must be aware of these biases and remove them from our data.

2)  Due to the interplay of random events, it is not possible to accurately and consistently predict future events.  However, randomness may work to your favor and you may accurately guess a few predictions.  However, in the long run, randomness with work to disrupt your predicting ability.  The best guess for a prediction is the mean because it will come closest to the real value than any other option. 

3)  I (Mara) had some systematic effects including slight fluxuation in the timing of taking birth control which would effect hormone levels.  I also took some extremely hot showers for extended periods of time over the five day period. 

7 sources of random variation:

1) Variation in the temperature of Chandler

2) Outside temperature

3) Briskness of walking between classes

4) Hotness of food (hot tea vs. ice tea)

5) Time of Eating (in relation to temperature-taking)

6) Exercise- causes an increase in temperature

7) Sickness- causes an increase in temperature

 

Strengths:

Both of us were fairly reliable about remembering to take our temperature and also to not take reading too close together.  The use of a digital thermometer increases the accuracy of the readings. 

Weakness:

Few conclusions can be drawn from this experiment because it covers such a small sample size.  Randomness would play too strong of a role in this size experiment to assign significance.  The sample size needs to be much bigger in order to reduce the effects of randomness.  Assigning significance to this data would falsely apply the law of large number to a set of small numbers (Hastie and Dawes 2001). 

 Systematic effects must be eliminated to ensure there is no bias.  As psychology majors, we are aware that millions of Americans are on antidepressant and antipsychotic medications that can reduce their bodies temporal regulation (McKim 1999).  If we were to conduct this experiment on a larger scale, these individuals would need to be screened for an eliminated from our data to remove this possible systematic effect.

As for our mini-experiment, we may want to impose rules such as “do not take your temperature within twenty minutes of eating, showering, exercising…ect.”  This would create more uniform data, but would likely reduce compliance.

 Referenced Sources:
Hastie, R., & Dawes, R. E. (2001). Rational choice in an uncertain world. The psychology of judgment and decision making.

        Thousand Oaks, CA: Sage, Inc.

MacEwen, B. (2008).  Randomness- lecture.  Chandler 304

McKim, WA (1999). Drugs and behavior: An introduction to behavioral pharmacology (4^{th  Edition). New York:  Prentice Hall}

^{I hereby declare upon my word of honor that I have neither given nor received unauthorized help on this work.}

^{Mara Rice}

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