Data Analysis: Grumpier Old Men In Comedy

However, we must perform some analysis on this data to confirm that the results for our class really are significantly different from the average. To do this, we performed a chi-square analysis on our data. Our chi-square value is 14.733, and the degrees of freedom are 6. The resulting p-value falls between 0.05 and 0.02. Therefore, we conclude that the data from our class indeed does not fit the average.

The quantitative subjective data is collated and organised into forms of a line graph, table values, and the calculation of mean and median data to determine if there’s any form of deviation of data. This will prove if there’s a linear or non-linear relationship between the data and test if there’s any similarities between the data values and/or the overall skew of the graphs. The outliers will be also added onto these graphs and will be compared towards each other recognising if there is a similarity or contrast in data and in relationships between both of the data. This will determine if the hypothesis of “family size has an

The data have information from two courses taught during the 2014/15 academic years with a combined enrollment of 76 students. These courses have a similar structure in that they met on Monday, Wednesday and Friday for 10 weeks and they both require students to complete online quizzes prior to each class. In addition, the final grade of both courses is composed of operating grades, midterms, and final exams. That is, there will be more than one factor to affect the final grade in these courses. In order to protect students, all students are shown in the database as ID number instead of their real names.

quickly generate the reports and graphs of long statistical data by using different analysis variable. This helps the user to get the desired outcome in short span of time with less use of computing skills and knowledge which means the user doesn’t have to be a computer genius to get the reports that are necessary for the decision-making.

Then we graphed a scatterplot, graphed clusters of dots, which represented the values of the two variables, on the ratings people gave for eating at home verse ones eating out. We got the mean, the arithmetic average of a distribution, median, the middle score in a distribution, mode, the value in the set that occurs most often, range, the difference between the highest and lowest scores in a distribution, and standard deviation, a computed measure of how much scores vary around the mean score, for the data we collected. For communication at home we were given the scores, respectively: 9,4,4,2,2,7,2,5,4,9,2,8,6,7,4,3,9,9. For communication eating out we were given the respective scores: 7,3,6,2,2,6,1,5,6,8,3,7,6,3,7,6,5,4,5,6. So for communication at home, we got a median of 4.5, a standard deviation of 2.74, a range of 7, a mean of 5.4, and a mode of 9. For communication eating out, we got a mean of 4.9, a standard deviation of 1.97, a range of 7, a median of 5.5, and a mode of 4. Then when you reached a correlation, a measure of the extent to which two favorites vary together, and thus of how well either factors predicts the

In this study, I chose to participate in the Presidential Popularity IAT and the Gender-Career IAT. In the Presidents study, I was required to recognize photos of Barack Obama and Bill Clinton and then categorize both with bad and good words (i.e. Barack Obama with good words and Bill Clinton with bad words, and vice versa). In the Gender-Career IAT, I had to categorize female and male names with either words associated with family or with career (i.e. female name with family words and male name with career words, and vice versa).

Second, they are to formulate a testable hypothesis by selecting a variety of Disney characters to postulate the study. During the third analysis, researchers will perform the experiment of the tested hypothesis. Last, they will, determine the conclusion of the study. Two independent coders examined Disney animated films to identify older characters of 55 years and older along with their characteristics. During their examination, the researchers viewed seven randomly selected movies independently to calculate the above stated variables of the characters. In calculating the variables, 34 Disney films were analyzed the first conducted research

Table 5 illustrates the cross over frequency for our individual, group, and section data based on the formulas listed in the methods. The individual and section data turned out to be very similar, while the group data was about 9 percent higher. We also used the formula for the mapping distance as listed above to calculate the map units. Again, the individual and section data are similar, while the group data is about 4.5 map units higher. Based on these results, the individual, section and class data are all proven to be very similar while the group data is slightly higher.

Mode/median: these two data were very similar scores. Sex had a mode and median of 0, age had median of 112.5 and mode of 113, prim dis mode and median of 1 and lastly, therapist mode and median of 2.

In order to properly analysis a graph, one has to consider all aspects of the visual analysis. Cooper, Heron & Heward (2007) states that a person has to “determine (a) the number of data points, (b) the nature and extent of variability in the data, (c) the absolute and relative level of the behavioral measure, and (d) the direction and degree of any trend(s) in the data” (p.150). Trend level (c) and variability (b) are the two visual analysis that this paper will focus on. It’s imperative that a researcher consider the importance of variability because this shows how much control they have over the factors that influence the behavior. In this particular graph, there is a high degree of variability. In the baseline data, the duration of the

\item Predict the final grade of a student based on the report of his or her alcohol consumption amount and other 26 factors from the data set\cite{c4}.

There are eight, 1 minute videos of children. Half of the children in the videos are three and the other half are five years old. The videos are also half male and half female. Each participant will have one passport-like photo for each video. There are four photos for each video: one matching the child at the same age, one matching the child but as an infant, one foil (not matching) the child at same age or one foil (not matching) as an infant. The four photo types will be randomly, but equally presented across all the videos. All four photo types of faces are seen twice, each in different orders. The photos will be presented with Qualtrics and the videos will be shown on larger TV screen.

The thirty data sets were plotted into a scatterplot and a linear regression analysis was used to show the

Participants were randomly assigned to either the romance-induced condition, the fear-induced condition, or the control group. These arousal inducing conditions acted as the independent variables, testing to see how they effected our dependent variable, misattribution. In all three conditions, participants were required to watch a short clip, and subsequently rate 30 neutral faced profiles. Beginning the study, the participants were seated to a computer, and each were assigned a link to a video clip, in random order. The first group (fear-induced arousal condition) watched a short clip from the film The Conjuring. The second group (romance-induced arousal) watched a clip from the film The Notebook. The final group, the control group, watched a short clip from the National Geographic film America before Columbus. The control groups’ film was a neutral/boring film in which there was no arousal stimuli. Afterwards, all the participants were asked to rate the same 30 profiles on attractiveness on a survey created in Qaultrics. All things considered, the experiment was built to examine the differences of mean attractiveness ratings, which was influenced by the condition they were

The data analysis focused mainly on the number of hours each participant in the study spent a week on Pinterest. From that data we were able to calculate the mean, median, mode, range, and standard deviation for both males and females, as shown in Table 1 in Appendix B below. The mean shows the average amount of hours for each gender that was spent on