Monty Hall Problem

The Monty Hall problem is when you have three choices and one of the choices has a prize behind it and you are told to pick one of the three options. After you choose your option the person will show you one of the options that doesn't have a prize. They will then allow you to either keep your first choice or change your choice to the other option.

When i played the game 10 times and stayed with my first choice i won 5 of the ten times and lost 5 of the ten times. Therefore i had a 50% chance of winning.
When i played the game 10 times and switched my choice i won 8 of the ten times and lost 2 of the ten times, allowing me to have an 80% chance of winning.
With these results relating them back to myth busters they are very similar because in myth busters whenever they switched their door they won more often then when they kept it the same.

After we played it ten times each we had to run a test of 1,000 times for each.
When we kept our choice during the 1,000 times. 34% of the time they won and 66% of the time they lost.
When we switched our choice during the 1,000 times 65% of the time we won and 35% of the time they lost.
Relating this back to myth busters this also helps prove the theory that when you switch your choice you have a better chance of winning.

My own thoughts about the Monty Hall problem is when I first heard what it was I thought there's no way thats possible because each choice has a 50% chance of being chosen. My first thought was this myth will be busted. Once they started running tests i was stunned at the results i was seeing. I was very surprised that they were right and that when you changed your choice you have a better chance of winning. I believe people stay with their first choice because of two reasons, either they like sticking with their gut feeling or they figure why change each has a 50% chance of winning because they don't know the whole truth about the numbers. Another game show that I think would be interesting is the game deal or no deal. You could analyze the same thing when it gets down to the last case to see if they stick with their first choice or switch the cases.

emperical rule

The emperical rule is also called the 68-95-99.7 rule. This is used on a bell shaped curve graph and you use standard deviation to label locations on the graph. The first line you draw in is the z score and thats down the middle of the graph. Then you have a standard deviation of 1 so theres a line for -1 and 1 and between those values is 68% of your data. With a standard deviation of two it's now 95% of your data and with a standard deviation of three its 99.7% of your data.
Example: It takes you 30 minutes to get to school and the standard deviation is 2 minutes.
Suppose a normal model is appropriate.
A) How often will you get to school less than 32 minutes?  Answer : 84%
B) How often will it take more than 34 minutes?   Answer: 2.5%

Extra Credit - Super hero project

Cheetah girl was born in Brooklyn New York in 1970. After reaching the age of 23 she was bitten by a cheetah which gave her super powers and stopped her from aging from then on. Its powers are invisible, extremely fast, and she can fly. She first discovered her powers when she was walking down the street to go to the grocery store when she heard a cry for help. This old woman’s purse was stolen by a thief and immediately cheetah girl said she would track them down. At this moment cheetah girl realized she was born to be a super hero. Without cheetah girl that sweet old lady would’ve never got her purse back.

Lil Games

Partner - Brandi Emerson

In class we played three different games with a partner and recorded scores randomly for the different games for our class. For example we used the 4^th score on bashing pumpkins, the 5^th score on Simon says, and the best score out of five on snap shotz. Using that data we created the following graphs and frequency distributions to display what we found.

1) Bashing Pumpkins - Freuqency Distribution & Histogram

 2) Simon Says - Relative Frequency Distibution & Frequency Polygon

 

 



3) Snap Shotz - Cumulative Frequency Distibution & Ogive

4. Best Game- Bar Graph and Frequency Distribution Table



gummi bear blog

 

The goal of the experiment is to see if there is a difference between launching a gummi bear while it sits on the rear end or if it is launched from its back. There are two levels which are lying on its back and sitting on his butt. The two factors we are adding is the person who launches the gummi bear and the sitting position of the gummi bear. The four different treatments we have in our experiment are RJ butt, RJ back, Andrew butt, and Andrew back. Our randomization was based on rolling a dice to see who launched first then we went in a counter clockwise order to see who launched next. The way we collected our data was by making a data table and recording the measurements of the launches. The way we measured the distance was by counting the tiles and we count up until the tile the gummi bear landed in.

The mean of RJ butt is 5.1 tiles, the median was 5, and the range was 12.

The mean of RJ back is 6.7 tiles, the median was 6, and the range was 11.

The mean of Andrew butt is 4.53 tiles, the median was 5, and the range was 5.

The mean of Andrew back is 5.2 tiles, the median was 5, and the range was 6.

The inferential statistics we collected was that Andrew on his butt was the most consistent data we collected. The most inconsistent data we collected was RJ on his back.  Therefore if we are doing this experiment to see if there’s a difference between launching it on its butt or on its back we can conclude that when you put him on his back he shoots farther.




 



• The difference between data and statistics is that data is what you collect and statistics is what you do with it. Example : We surveyed 50 people to see what their grades were on their last stats test. We found 30% of the students received A's while 44% received B's .
• The difference between Population and sample is that your sample comes from the population. The population is the entire group while the sample is a portion of the group. Example: you survey your stats class , the class would be the sample and the population is all of the MHS students. 
• The difference between parameter and statistic is a parameter describes a population while a statistic describes a sample. For example if the population was 20,000 and only 150 were selected as the sample then the population size of 20,000 would be the parameter and the sample size of 150 would be the statistic .
• The difference between descriptive statistics and inferential statistics is that when you use descriptive statistics (charts, averages,  graphs, etc) to draw conclusions you are making an inferential statistics. An example of this would be if you had a graph and it showed 50 people spent more than 1,000 dollars in a month on television .
• The difference between qualitative data an quantitative date is that quantitative consists of numerical measurements and qualitative data doesn't consists of numerical data rather it consists of labels and attributes. For example the price of an apple would be quantitative data. The number on my soccer jersey would be qualitative. 
• The definition of census is when you collect data from an entire population. 

E: The activity I completed over the last two days was about surviving a plane crash in Canada and ranking the items for their importance to survive. We were given 11 items that were essential to surviving in the wilderness. First we ranked the items individually and then we compared with a group and re ranked them as a group. After that we got the experts rankings of the items and then found the absolute value difference between the experts rankings and our individual rankings. Following that we found the mean(average) for our absolute value difference and wrote our average on the board by gender. Last we found out who the ultimate survivor would be and we found that by seeing who had the lowest average. 

F: My group would have survivied very well based on the rankings we did for the supplies. When i calcualted the absolute value difference of my groups rankings and the experts rankings the highest difference we had was five. For six of the items our absolute value difference was one or less. The mean for our absolute value difference was 2.27. Our group had the right mind set with almost all of the items except for the crisco because we had that as number nine and it was ranked number four by the expert. Overall my group would have survived very well if we were stuck in this situation. 

G: If i was stranded in Canada I wouldn't have survived very well. My mean for the absolute value difference was four. For a lot of the items I had them completely wrong. The lighter I had as number 11 but the expert ranked it as number one. Another item I was very off of for my ranking was the pistol I had that as number two but the expert had it as number nine. This activity showed me how bad with nature and the outdoors I really am because according to this activity I wouldn't have survived very long at all.