Stats at the Movies

The article is talking about a movies Rotten Tomato rating and how it compares to its actual gross sales. Brendan Bettinger is saying how some times the Rotten Tomato rating is spot on with the movies domestic box office sales, like the Transformers movie had a rating of 35% and had sales of $350 million where Warrior had a rating of 83% and it's sales were just over $13 million. But there where several other factors to consider and that's just what he did, Bettinger figured out the top five contributing factors to a movies gross sales and included those in a formula with the Rotten tomato rating to get the movies gross sales. In conclusion Bettinger says that positive reviews equal financial success. Say someone likes a movie, then they will go and tell people about it and those people will have a higher chance of going to see that movie and vis versa with a bad movie.

My thoughts on this article is that overall it had some pretty interesting things to say about how to relate certain things to a movie's gross sales, most people wouldn't even put a thought into it. And Bettinger shows that not one thing contributes to the results, that there are many factors involved and he took the time to figure those factors out and put them into a formula and his formula is almost spot on the movie's gross sales, I know I would never have the patience to do that, but find it cool that he put an everyday thing such as going to the movies, into statistics.

In the article it has several things relating to what we are currently learning in AP Stats class right now. Things such as, Bettinger made a scatter plot of a movies rating versus their gross sales, with those points he drew in a line of best fit which shows that there was a strong positive correlation, but what is the correlation. Bettinger found out the slope which was .68 to also prove that there is a strong positive correlation between the two but it wasn't a perfect correlation so there are obviously other factors involved in the movies gross sales.

This article is also involving stats that we have yet to learn such as figuring out what the other factors are and including them with all the other factors. We have just so far learned how to deal with one factor and how much that one factor relates.

The movie Moneyball came out in 2011 and based on the formula; GROSS= -80+0.6xRT+0.5xBUDGET+0.025xTHEATERS+50xSEQUEL+20xPG13. Moneyball's RT rating was 95%, budget was $50 million, theaters was unknown so we went with the number Bettinger used which was 3450, this movie isn't a sequel and the movie is PG13. The predicted gross sales is $27 million but I'm pretty sure I put the numbers in wrong, I was confused on what to put for PG13 and theaters so I'm pretty sure my results are wrong, that actual gross sales were over $110 million. A movie that's coming out in three months is Les Misérables but it doesn't have a rating so we can't really predict the gross sales, we are missing too much information to do so.

Infographic

My infographic as you can see is all about cheerleading? Now why did I choose cheerleading? Because cheer is my passion and I've been cheering since I was three years old, I wanted to prove some points about cheerleading. My first graph shows what age they started cheering, many started out very young, most were 3-5 years old. My second graph gets into if you think cheer is a sport. Now there are two different types of cheerleading, their is sideline cheer, which is what you have a schools and then there is competitive cheer which is were you go to an outside gym and you compete. Me personally, I don't see sideline cheer as a sport because you just stand there and say some cheers how ever with competitive, I get worked up when people say competitive cheer isn't a sport because we put in a lot of effort and work, and exert a lot of force in competitive cheer, I would like those who say competitive cheer isn't a sport to actually try competitive cheer and then see what they say. But in my graphs, you can see that just like me, many people think that sideline cheer isn't a sport but competitive cheer is. I wanted to show that there are guys who do cheer, there aren't very many who do competitive cheer, only 3% are guys but what really shocked me is that 50% of cheerleaders are guys on college cheer squads. My last graph is of injuries and to show how cheerleading is a dangerous sport, out of 1116 injuries (including every sport), 739 of those injuries were cheer injuries, that's 66%. So cheerleading is very dangerous, I know from experience as well because I've broken several toes and fingers as well as dislocate my elbow and knee all from cheer. My color scheme for this infographic are the colors of my cheer squad, blue and orange. Cheerleading is my life.

5 W's and How

Earlier this week we learned about the five W's and How. They are who, what, where, when, why and how. Each one helps us determine information about our data. The what is the most important because it tells us what kind of data is being collect and the type of units. The what is then put into two different types of variables. There is a categorical variable which is characteristics and then there is quantitative which is numbers. But you got to be careful with the quantitative because some numbers sad categorical. A way to determine if the number is quantitative or categorical is if the number can be measured, if yes then it's quantitative. It the number is giving a characteristic to something, then it's categorical. The who is also important because it tells you who collected the data and from who did you collect the data. You can collect the data several ways. Some are; surveying people, this people are then called respondents, experimenting on people, they are then called subjects or participants and then you could experiment on other thing like animals, plants or objects, those are then called experimental units. The who helps you determine who was the data collected from. The 5 W's help you determine information about the data, who collected or from who, what was collected, where was the data collected, when was the data collected, why was that data collected and how was the data collected.

AP Stats So Far

So far in AP Stats, we haven't done much so I don't have much to go on when it comes to my thoughts about AP Stats. I do like my teacher, Mr Mays and the complete nerd he is. I'm ready to get into the actual learning of stats. The assignment we are working on now is kinda simple and easy, which isn't always a bad thing. But I like a challenge and math is my best subject and I'm waiting for that challenge. It's still very early in the year so I understand why we haven't got into a lot of stats. So I'm just giving it time. I think I'll enjoy AP Stats.

I Survived

Over the last two days in AP Stats we did an activity of ranking items of most importance when surviving and then compare them to group and expert rankings.
Our group would've been alright surving. We had some items that were dead on with the expert such as the newspaper and the clothes. But we also had items that were way off, such as; the lighter, the expert had the lighter at a 1 where our group had it as an 11. All the other items were in the ball park. Our average differnece was 3.82.
Individually, I would do a little better than my group when having to survive. My average difference was only a 3.27 where our group was 3.82. Some how I beat the males average as well which was 3.28. Just like the group I had items that matched the expert and items that were complete on opposite sides. The lighter is what really tripped me up because what am I supposed to do with a lighter with out fluid. I'm not the expert I dont study survival skills. But based on my rankings I would survive alright. But me personally, there's no way I'd survive, I'd go crazy.