--Original published at Emily Garvin's Psych Blog

For this first impression blog post I chose to watch the myth busters video that studied if women were more successful at reading emotions than men. To test this theory the myth busters took photos of the team members making different facial expressions. They then showed these photos to men and women and asked them to decipher the emotion of the facial expression by just looking at their eyes. Not surprisingly, women were better than men when it came to reading facial expressions, but they were only superior by 1%. To explain the results of this study the myth busters referred to previous theories involving the emotional and memory centers of women’s brains. This part of the brain is proportionally larger in women which allows women to recognize and respond to emotion faster than men.

The myth busters planned and executed their experiment almost flawlessly. However, I do believe that the myth busters could have used the additional data they collected to better explain this phenomenon. I thought the idea of just showing pictures of the team member’s eyes was effective because it was more relatable to a real-life scenario. When engaging in a conversation with someone eye contact is key. To read someone’s facial expression you are most likely to look at their eyes first. I know the myth busters timed how quick the men and women responded, but at the end of the video they did not discuss these results. If they would have discussed the varying time results they could have talked more about the brain and explained the real reasoning behind why men are not as accurate at reading emotions.  Nevertheless, I believe that overall the study was performed with proper research methods and the myth busters received the results they were ultimately searching for.

--Original published at MaddiesCollegeBlog

For my first impression post, I decided to choose the second option which involved choosing a video that was done by the popular group “The Myth busters”. The video that I decided on was ‘Is Talking on the Phone While Driving as Dangerous as Driving Drunk?’. What they did to test if this question was plausible, they had two people would drive a certain course that had multiple different obstacles placed on the track, and the first time they went through it, they completed it without any distractions. Then, they drove that same course and completed it with the distraction of talking on the phone but, that person was giving them with different tasks to complete while also trying to drive. For the third and final course, the testers consumed a distinct amount of alcohol and attempted to complete the course. Each time they completed the course there was a driving instructor that accompanied them in the car that made the judgment if they passed or failed the test.

Before watching the video, I was under the strong assumption that obviously driving under the influence would be a lot worse than just talking on the phone. Though, the  experiment exemplified that both of the test subjects impacted the drivers ability to complete the course in a positive manner (both of them failed the test when on the phone and under the consummation of alcohol). The results showed that both failed the test by a greater amount while on the phone, and not just intoxicated, which was totally shocking to me. Yet, I did expect both to be significantly bad, I did not expect them to be so far off. I feel that the results of the experiment could have been skewed due to the setup of the experiment, but that can be easily fixed if the experiment were to be repeated.

Two main issues that I noticed with this experiment all around was the fact that there were only two test subjects, everyone knows that in order for the experiment to get more accurate results, you need to have multiple test subjects and multiple tests in general. The more amount of tests with more amount of test subjects will allow the experiment to  have a better chance at accuracy. Another issue with this experiment is that I feel there is a drastic difference between test subjects. whether it be gender, weight, and even just one’s mind and body. Everyone is very unique in their own way, certain things like completing a task and drinking an amount of alcohol can impair people in different ways, so I feel that depending on what the test subjects are could have skewed the results. Which is another great example of why you need multiple trials in an experiment.

--Original published at The Core Techs

MythBusters, a popular television show from Discovery Channel, has plenty of mini-myths which help debunk many wives’ tales and other rumors. Although each mini-myth is highly captivating, people should know that Hollywood cannot always be trusted. Here, we are going to be critiquing one of the MythBusters episodes, “Does Weaving Through Traffic Actually Get You to Your Destination Faster?”

The episode starts out by explaining the old tale: Weaving through heavy traffic will not make a difference in getting you to your destination faster compared to if you stay in one lane. In this case, the Busters begin their experiment with two different cars: the weaver, and the non-weaver. Both cars must travel the same route at the same time, and the goal is to see who will make it to their destination first. After making many lane changes, stressful decisions, and frustrating other drivers, the weaver and non-weaver end up at their destination at nearly the same time. So there it is; Myth proven true! Or has it been? There are many strengths and weaknesses to this experiment.

Their strengths come from many different aspects. For example, setting both trials under the same conditions was a smart idea. Both cars were to take the same route at the same time. Driving conditions were identical. If they had taken different routes at different times, this may not have been appropriate as driving conditions could have changed, giving advantage to one and not the other.

Although this is true, there are many weaknesses that could have been improved throughout this experiment. For example, MythBusters only conducted one trial. In order to get a solid conclusion, they could have conducted the same exact experiment a few more times to compare, or they could have changed the drivers. The car make and model should have also been the same. Different cars have different functions. Locations matter too; Perhaps they should have performed more than one trial on different roads. It is better to provide multiple scenarios and trials when making a conclusion on hypotheses such as these. Getting more information from more widespread places is beneficial because perhaps the myth proves to be true in one place, but not in another.

What do you think, Core Techs? Does weaving in and out of heavy traffic get you to your destination faster or not?

Stay safe on the roads!

-B

upload.wikimedia.org

--Original published at JD's Blog

My first impression post this week will discuss the popular show known as Mythbusters. The topic I choose to critique was a small clip titled, “Do Beer Googles Really Exist?” In this segment, the Mythbusters tested to see if alcohol has the ability to mess with a person’s mind. In doing so it would cause them to think other people looked prettier than they would if they saw them while sober. They devised an experiment where the show’s hosts rated people while sober, then rated similar people after catching a buzz and finally ran the same test a third time after consuming a mass amount of alcohol. Overall, I thought the experiment was well planned. All of the hosts drank a similar amount of alcohol and rated groups of people that were deemed similar to one another. However, I think this part of the experiment might be a flaw as well, because every person’s body responds to alcohol differently resulting in mixed levels of “drunkenness.” Another flaw I saw dealt with the people that were rated. They used a different group of people each time. This could potentially present a problem because every person looks different and might be received differently by the human mind. For example, during the second run of the test the girl on the show dropped her total points by almost half while the guys both went up. I think they should have used the same group of people throughout. Therefore, if the hosts thought the people were better looking, after each level of intoxication, they would’ve given the group a higher rating. I agreed with their results, they don’t exist, because alcohol affects everyone in a different way only sometimes resulting in, “Beer Googles.”

--Original published at Anneka's Blog

This weekend, I watched a Mythbusters video clip where Jamie and Adam test out whether or not hands-free devices are safer to use while driving versus hand-held devices. To test this question, the pair each drove through a driving course talking through a cellphone, and then a hands-free device. The results were that the average score for both independent variables was a failing grade, and the scores were almost exactly the same with a 0.5 point difference. Then, to improve the experiment, they paired with Stanford University Automotive Innovation Facility to test 30 drivers on a simulation with a hands-held and hands-free GPS system. The results yielded similar results where hands-free devices were no safer than hand-held ones.

This experiment, as with many experiments, had its strengths and weakness. I liked that for the first experiment, on the driving course, the non-driving member had the driver talking and thinking simulating a real conversation, and that the course had a variety of driving situations such as parallel parking and turning. The main strength in this experiment was that Jamie and Adam discussed the results and the procedure of the driving course test and then found their own strengths and weaknesses. They then made adjustments to better improve their experiment. It shows that they are analyzing their own work and adding suggestions for future experimentations. Lastly, I liked that during the simulation test, they had equal number of drivers per variable for equal testing and a mix of gender and age to give more depth to the experiment.

One of the weaknesses in this experiment that I saw was less defined control variables. I would have liked to have seen in both the driving course and simulation a group of drivers take the test without using any devices to see the scores the drivers would get without distractions as a base line. This would show the driving ability of the participants and the difficulty level of the simulation. From my own and high school classmates’ experiences on driving simulations, driving in a simulation is a different experience. I am interested in knowing what controls they had for the experiment if any such as difficulty level or equipment type since they did not include this. Additionally, I believe more real-life “on the road” tests would be beneficial. Like a driving course with parking, turns, testing people actually driving cars with talking, texting, and GPS navigation. This would increase the data amount versus just one simulation run. This way one could see how safe and aware people are on the road. Third, a variety of tests would strengthen this experiment. For example, testing reaction and braking times could give more depth to a driver’s awareness and reaction time versus observable crashes. Fourth, I thought splitting the participants in half per variable, decreased the safety testing. If all 30 took both variables, it would compare driving ability per driver much like Adam and Jamie during the driving course. Lastly, I am interested in the Mythbuster’s personal hypothesis on this topic. The show covers general myths, but adding Jamie and Adam’s thoughts on the myth would add to the scientific method.

--Original published at Sarah's Blog

I watched a clip from the TV show Mythbusters titled “Does Weaving Through Traffic Actually Get You to Your Destination Faster?” They tested to see if staying in one lane was the fastest way to get to your destination, as opposed to weaving through all the lanes of traffic. When I first read the title, I believed that staying in one lane is a safer and overall faster option. In the video, Grant believed weaving through traffic was the faster option, but Tory believed that staying in one lane is quicker. To test their opposing hypotheses, the group of them split up into two cars: one weaved through traffic and the other car stayed in one lane. They evaluated this by driving along a highway to the San Jose Tech Museum, which was 46 miles from where their shop is located. The test was conducted during the morning rush hour at around 7:30am. At the end of the clip, they were only through half of the test and the car that stayed in one lane was in the lead. The clip only showed half of the test, which was disappointing as I wanted to see which car won.

This experiment was very simple, and overall it gave an idea as to which one was faster. They used a long enough route to examine which way getting through traffic was faster. They also had both cars drive in the same rush hour, which made sure they had basically the same drive besides the weaving/not weaving factor. Also, the team made sure to document the thoughts and feelings that both Keri and Tory were having while driving in this test. Some weaknesses this experiment had was that they only tested it once. Tory, Keri and Grant should have tested it during both the morning and the night rush hours, as they could have different characteristics. Another weakness was that I believe they should have tested more than one driver. Doing this could have shown different results than just the one test.

Overall, this clip showed the experiment and it did show which way was faster to get through rush hour traffic. I wish they showed the last part of the experiment, so we could see which one was faster at the end.

--Original published at JanellesCollegeBlog

For my first “First Impressions” blog post, I decided to watch a mini-clip from the popular TV show called Mythbusters. I chose to watch the clip to see if increased tips in a restaurant setting was caused by increased breast size. In this clip, the female host of the show was disguised to be a barista at a local coffee shop where she was sure to receive a lot of tips for her service. The experiment was conducted over three days, and each day the host of the show gradually increased the size of her breasts-starting with the control of her own breasts and then increasing to a D-sized cup. Then, the amount of tips were tracked by the other hosts of the show from video footage in the coffee shop.

There were many strengths evident within the clip mainly the standardized variables that were held constant during the experiment. For example, the host of the show wore the exact same clothes for the three days as well as the same wig and contacts. This was done to try to ensure that the only factor affecting the amount of tips that the customers gave were only dependent on the breast size of the waitress. The other standardized variable that was extremely important was that the waitress worked the same shift every day. This was done to ensure that the same amount of hours were worked every day so it would not skew the amount of tips received. Also, this was done to try to control the factor of not knowing who or how many people will come into the coffee shop on the given day. Although it is not 100% certain that the same people will come in every day, most people tend to stick to a daily routine including getting coffee, so this is the best way to try to standardize this variable. The last of the standardized variables was that the barista gave the same level of service to every customer. This was done to ensure that the tips given were solely based on breast size and not on the way that the barista was treating the customers. Finally, the last strength of the experiment was the data collection and analysis. The hosts used video to record who tipped and in what amount so that they could collect specific data that would be analyzed later. They needed this data to determine the increase in tips given as well as the difference between the amount of tips that each gender gave. For example, through these observations and records, they could determine with increased breast size, the amount of tips that males gave increased by 30% while the amount of tips that females gave increased by 40%.

The biggest weakness that was evident in the clip was that it was impossible to control who came into and out of the coffee shop. For example, it was impossible to control the amount of people that came in on any of the three days. If more people came into the coffee shop on one day over another, then there would naturally be a greater amount of tips for that day. Also, the experimenters could not control the gender of the customers. If females tipped more with increased breast size, then more money would be made if the majority of the customers were female. These kinds of variables could not be controlled in this experiment, but a way to try to control it would be to count the amount of customers and their genders and have a set amount for each day. For example, they could have set the sample size to be 50 females and 50 males each day. This would standardize the uncertainty of the gender differences in tipping as well as if more people came into the shop one day over another. Another weakness in the clip was that it was only one person that controlled her breast size. This could be solved by performing this experiment at different coffee shops or with different women. Finally the last weakness was that many individuals tip for different reasons. Although, the hosts tried to standardize all the variables that they could, many customers tip for different reasons and some people are more stingy with their money than others. Also it is a general rule that the greater amount of money spent, the more you should tip, so the amount of tips would also depend on the amount of money that was spent by each person. This variable is extremely hard to control and would only be solved if they could make sure that the same people came into the coffee shop for each of those three days and ordered the same products each time.

Overall though, the conclusions from the experiment were able to prove the experiment plausible and show that the larger the breast size of the barista, the greater tips she will receive.

--Original published at Jessie's PSY105 Blog

I chose the second option for this week which involved choosing and critiquing a Mythbusters clip. The clip that I chose was ‘Is Talking on the Phone While Driving as Dangerous as Driving Drunk?’. To test this question, two of people would drive a course that had various obstacles without any mental/physical impairment added. Then, they drove the same course and completed the obstacles while talking on the phone to someone that was providing them with various tasks (such as repeating sentence back to them). Finally, the course was driven a third and final time after the subjects consumed a certain amount of alcohol. Each time, there was a driving instructor in the car who judged whether or not they passed or failed the course.

Before watching the video, I assumed that talking on the phone would definitely be difficult for the driver but would not be as impairing as driving while drunk. While their experiment showed that both of the variables negatively affected the driver (as the test was failed by both drivers when on the phone and when drunk), it was mentioned that they failed the test by greater margins when talking on the phone. I found this quite surprising. Not so much that talking on the phone resulted in worse results than driving drunk, but in that the margins were so much larger. I think that this could be in part due to the set up of the experiment. While they did have an adequate control, in the form of the first run of the track without any impairments, there were some areas that were lacking.

One problem I saw was in the test run after they consumed alcohol. They did not mention in the video how much alcohol they consumed or what the results of the breathalyzer were. I would assume that if the levels of alcohol consumption had been larger then perhaps the results would have been more comparable. Another potential problem that I saw was in how the experiment was not repeated. Each run was only done one time which would leave a large amount of room for error. Overall, I found the results a little bit surprising and while there were some errors in the execution of the experiment, I do not feel that the results would be too different. Ultimately, it can be concluded that both talking on the phone while driving and driving while drunk are very dangerous.

--Original published at Madison's Blog

For my first impression post this week, I chose to critique a Mythbusters episode about “Are Women Better at Reading Emotions than Men.” In this study, the hosts all took pictures of themselves making different emotional facial expressions with a camera and cropping them down so just the eyes were showing. They each portrayed “confused”, “angry”. “happy” and “sad” emotions. After the pictures were cropped and randomly placed in a slide show format, volunteers were ushered in one by one to test the hypothesis that women were better than men at guessing the emotion.

Some critiques I have about the study set up, is that the scientists never disclose to the viewer how many of each gender are tested. It is always better in science to have a large sample size for experiments in order to have more precise data. For all the viewer knows, maybe only ten of each gender were tested, and that means there is more margin for errors. The results of the study could possibly be discredited if a larger sample size was used in a different experiment testing. The unknown sample size makes me question the validity of the results drawn. Also, only four people’s emotions were used in the pictures shown. The test subjects only saw the same four people’s different emotional eyes, which can cause the question of “can they tell the emotion, or are they using process of elimination?” If the same person’s eyes appear more than once, but you already guessed the emotion “Happy”, that means you won’t again guess the same emotion, even if logically you believe it to be. Using the process of elimination, you wouldn’t guess the same emotion twice if you could tell it’s the same person’s eyes. The scientists should have had more variety in the eyes photographed, so the test subjects could see a more various range of emotional eyes. Having a greater range of eyes, with the emotions, could have had an effect on the results.

Some of the methods used for the experiment were very interesting and worked. I admired the idea of using just the eyes to portray the emotion, rather than a whole picture. The mouth of the person in the picture could have given away the emotion quicker than they eyes can. Only showing the eyes led to more thinking involved for the test subjects. It allowed a wide array of answers to be given for each set of eyes. I also thought that the age range of the test subjects was a plus for the study. From the video, you could tell that the ages ranged quite a few years between each male or female being tested. The difference in age helped validate that it wasn’t just one age group of a gender that was better at seeing emotion, but it was actually the average of the group. When everyone was tested, the scientists averaged each gender’s scores, and it ended up that women were better at seeing the emotion than men. For me to actually believe this claim though, I would need more studies to be done and more conclusive results found.

--Original published at KatiesPerspectives

For my first, First Impressions Post, I decided to watch a short clip from the popular TV show Mythbusters highlighting the phenomena that women are better at reading emotions than men. In this clip, the hosts of the show sat in front of a camera and portrayed a number of different emotions from happy to sad to angry and confused. The photos were then developed and cropped down so that only the eyes of each picture were visible. Volunteers (both men and women) lined up outside the door of the Mythbuster studio to be asked the question, “What emotion is this person portraying just based on their eyes,” and the results were absolutely astonishing.

Some of the weaknesses I found with this experiment all surrounded scientific and methodological validity. Although the experiment seemed to have it’s disadvantages and added a bit to my main gripe with this experiment, how many people (and of each gender) were being asked the question? The more people that volunteered to be involved in this study, the more accurate the study would be. If more of one gender showed up to participate in the study, then one gender’s results would be more precise than the other. Although the Mythbusters might have considered this in advance, they failed to specify and for that reason, I was forced to question that sort of validity in the study. A solution to this would be to collect data from more people, and if they hadn’t already, make it so the gender ratio is even within the study. Although there were a total of 17 pictures shown to the volunteers, they were all of the same 4 hosts from the show. This unveils the issue of woman or men being better at reading emotions in general vs. learning the emotions of a certain person. By viewing multiple pictures of the same people, one might have the ability to retain prior information based on this person’s previous emotions and thus, rethink what they think vs. what they feel about a person’s portrayal of emotion. A was one could fix this problem would be to have 17 (or more) pictures all of different people.

Although there were some weaknesses in the experiment, there were also quite a few strengths that I appreciated one being the independent variable being held constant. The independent variable was that of the photos all being the same for each of the volunteers regardless of their gender. This made it so every person interviewed had the same visualization to work with and so that one person didn’t get an easier-to-read picture than the next. Another part of this study that I actually really appreciated was the fact that the pictures that were shown were of the eyes of both men and women. Although popular opinion might say that it’s easier to sense emotions of people within your gender, this sort of variable eliminates the chance of that being a factor. In the end, the results were clear and the average was taken based on the results of each gender. Men had an average of 9.6/17 while women prevailed with 10.6/17.

Many strong and valid techniques of performing this study were used and for that reason, I think this study was overall a success.