Maths Statistics Project

Our topic is on, Television. We are studying what the year 9 students at All Saints’ favourite genre of television is and how many hours they watch television per week. We are also using a demographic question and studying what the most preferred genre of television is for each gender and comparing this between the non binary, females and males. Our categorical question is “What is your favourite genre of television” and our numerical question is “In a typical week, how many hours of television do you watch”.

Our rationale (reason) on why we chose this topic to study was because this topic would be helpful for the media and advertising agencies because they can use this sample data to target advertising to different audiences and see what genres a typical 13 – 15 year old enjoys. As well as figuring out what gender prefers what genre of television.

The results for this investigation that would be interesting is to find out the average amount of television that Year 9’s watch in a week and because there was a couple errors in the data that we could use for our presentation. This topic will help us to understand what genre All Saints’ students enjoy and how much television students watch in a week.

The sampling method:

• Convenience sampling because it was easy and accessible to survey all the students in our year as we all do math’s
• Sent out a survey to all the students in year 9, this was done through Microsoft Forms

Sample Size:

• The survey is the whole population of year 9’s in All Saints’ and all of year 9 filled out the survey
• The sample size is 100% of the year 9 students

Evidence of bias:

• Many students may have changed their answer depending on what their friends put in.
• This can be proven as the forms were filled out, in class siting next to our friends or peers.
• Some students don’t take the survey properly and put funny answers leading to outliers.

Measures which have been taken to avoid bias:

• The measures taken to avoid bias from occurring is making the survey anonymous, so that when a person would fill in their answer it wouldn’t show who did what. That way they had little peer pressure about their results to change it, so that social desirability bias can be avoided.
• The survey order is randomised for each student so that question order bias can be avoided

1. Categorical Results

• Mode: Comedy (skit, sitcom)
• Percentage breakdown of results:

Comedy (skit, sitcom) (50)	50/140 = 0.3571	35.71%
Crime/procedural (23)	23/140 = 0.1643	16.43%
Reality (5)	5/140 = 0.0357	3.57%
Thriller/horror (14)	14/140 = 0.1	10%
Fantasy/sci-fi (24)	24/140 = 0.1714	17.14%
Drama (11)	11/140 = 0.0786	7.86%
Documentary (8)	8/140 = 0.0571	5.71%
News and current affairs (5)	5/140 = 0.0357	3.57%

1. Numerical Data

• Mean: 8.63
• Median: 3
• Mode: 0
• Min:
• Max:
• Quartiles:

• Q1: 1
• Q3: 7

• Range: 42
• Interquartile range: 7 – 1 = 6
• Outliers present: (yes) 12345678

In these questions the interpretation of the question could be different as many people thought differently of what ‘Television’ meant.

The reason people may have been confused on the interpretation of the question is because some people thought of television, to also include platforms like YouTube or Netflix and others may only have answered the questions to only live tv, that may be why many of the answers were 0. This messed up the results of the numerical data because people have been basing their decision on different things.

In the categorical question, overall 35% of people chose comedy as their most preferred genre. Comedy was the most common choice amongst girls (25.75%), comedy was also the most common choice amongst boys (41.6%) as well as the most common choice amongst non-binaries (66.6%).  Therefore the most popular genre was comedy overall and the average amount of tv watched per week by Year 9s was 8.6 hrs. The shape of the distribution for the results in the categorical data were positively-skewed.

For the numerical question, 0 was the most common answer with 30 people answering 0. This is because the results were flawed as people had different understanding on what ‘television’ meant, as some people based their decision on live tv while others based their decision by including platforms like YouTube or Netflix. The shape of the distribution for the numerical data’s results was also positively-skewed to the right.

A potential explanation for the results is that comedy is a very popular genre and a genre that most people have watched and enjoyed, therefore being the most preferred. A surprising feature in the results, was that for the girls, crime was nearly the most preferred compared to comedy and all genders answered comedy as their most preferred genre of television.

The limitations of our work were that the options were limited, leading the survey to be answered inaccurately. For example the categories were: Comedy, Fantasy/sci-fi, Crime, Thriller/Horror, Drama, Documentary, Reality and News. As you can see there is no Action and Adventure, one of the biggest categories of television. The limitations were that the questions weren’t clearly stating what the types of TV were, leading the surveyed to be answered wrongfully.

We recommend that in the future the questions are inclusive of all the different genres so that people don’t have to inaccurately answer the question. Also that the program shouldn’t allow outliers as it would mess up the results since we can’t count that response. In the future the question should be more detailed as when thinking of television many think of live TV, and not things like YouTube and Netflix. This is a problem as many people answered the question thinking of different definitions of TV.

Our experience in this task was entertaining and knowledgeable as we learnt many different things that will be useful in our pathway to the future. We learnt how to display our data e.g. Dot plots and different ways to present. We had gained a better understanding on how to use excel. We learnt how to use demographic questions to analyse our data. We learnt how to present our data using infogram which could be used in the future for other projects and to show our data.