This is a report on the data that was collected using my survey that I created. For my qualitative question I asked which television show they would rather watch. I used a science fiction show, a political program, a music awards show and a sports game. I chose these because I wanted to determine what is most important in a person's life. For my univariate quantitative question i asked how many times a week people eat at a fast food restaurant. I was curious to see how many times people eat out because fast food is cheap and convienent. The last two questions I asked for the bivariate quantitative part were how many accidents they have been in and number of tickets they have recieved. I wanted to see if there was a positive relationship between the two. Below is the raw data table from the survey.
Below is the question I asked for the Qualitative Data. My variable is Programs.
 Which of these programs would you rather watch?
The Superbowl (Sports)
The Grammy's (Music Awards)
A Presidential Election (Politics)
Game of Thrones (TV Show)
Below is a bar graph of the collected data.
Below is a frequency table of the collected data.
Frequency table results for Programs:
Count = 41

Below is a pie chart of the colled data.
I asked this question because I was curious to see what shows are more important to people. I predicted that Game of Thrones and the Superbowl would be the most watched. It is disappointing to see how few picked the presidential debate. This could be the result of the presidential candidates this past election.
How many times a week do you eat at a fast food restuarant? My variable is Fast Food.
Below is the Mean, Median, Mode and Standard Deviation of the data.
Summary statistics:

Below is the frequency distribution of the data.
Below is the Histogram Data
Below is a Boxplot of the data
The upper fence of my data is 6 times a week and the lower fence is 1 times a week. I had one outlier with a total of 9 times a week.
The results of this question were surprising to me. I predicted that people eat out at least 3 or more times a week. The data is clearly skewed right with 13 of the reponses saying only once per week. This shows that people tend to cook their own meals instead of spending the extra money on fast food.
The questions I chose for my bivariate data was how many tickets have you recieved and how many accidents have you been in. My dependant variable is accidents and the independant variable is tickets.
Below is a Scatterplot of the data.
Below is the calculated correlation coefficient
Simple linear regression results:
Dependent Variable: Accidents Independent Variable: Tickets Accidents = 0.58447391 + 0.14136014 Tickets Sample size: 41 R (correlation coefficient) = 0.2334849 Rsq = 0.054515199 Estimate of error standard deviation: 1.0067194 Parameter estimates:
Analysis of variance table for regression model:

There seems to be no linear relationship between the two variable. I predicted that the more tickets someone would have would also increase the amount of accidents. As you saw by the scatterplot my data is all over the place. This is most likely a result of many lurking variables. I would say that the more tickets people get the more likely they be more careful drivers to avoid penalties. Thus reducing the amount of accidents.
I found this project to be very informative and fun. It shows the challange of actually getting people to take your survey. It seems getting people to take 5 minutes out of their time can be difficult. However, this really helped show me how to write up and analyze data into readable information. These types of reports will be of great use for future jobs.
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