Hypothesis Explanation
I came up with my prediction that the maximum distance travelled would have been 150miles by using logic- if they were to travel a greater distance than the one previously stated it would be likely to suggest that there would have been a National Park closer to their origin, making the journey to this one un-necessary. (An example of another National Park would be the Pennines)
I predicted them to be of an older generation because it is likely that people of a younger generation would be working during the week.
They are likely to be older females because there are far fewer males of this age as many men who would have been this age may have died in either of the World Wars. Another reason for suggesting this is because of statistics. Statistics show that the life expectancy of males is less than that of females.
The purpose of visitation would be Tourism as they are likely to be retired and may consider this a way to spend their free time.
The method of transport used will be coach because they may be too old to drive a car for themselves or it may be easier not too. It is also likely that they will be travelling with a “club” or friends.
Aim
My aim is to try and prove my hypothesis correct. To accomplish this a survey will take place within the area itself-taking the form of a questionnaire, which will be used to collect the required results, to help with our investigation. The results will be collated and then we will present the data in graph form so that is easier to analyse.
We, the students, will design our questionnaires in school and carry out the survey in the village of Betws-Y-Coed, on a random select basis-each student surveying a minimum of 25 people.
The survey will be carried out on Tuesday 9th October 2001.
Method Map
About the Questionnaire
The surveys will be carried out, by Wirral Grammar students, between the hours of 11:00am and 2:30pm, on the 9th October 2001
The questionnaires themselves were previously designed in class. The questions were prepared for later interviewing of respondents.
The selection of respondents will be random. The people carrying out the surveys (a.k.a the “Questioners”) will stand in an allocated area and asked every third person who walks past to participate with the survey.
Each student was required to interview a minimum of 25people each.
A clipboard and an upside-down plastic sheet will be used for convenience and protection of the questionnaire.
A sample of the questionnaire can be found on the sample chart.
Instructions of how we are to fill can be found on the next page.
How the questionnaire is to be filled in
- The questionnaire is to introduce himself, and what he is doing.
- The respondent is asked if they had previously participated in a questionnaire by one of our classmates.
- If they answered
- Yes: The questioner thanks the person for their time and begins the random selection method once again.
- No: The Questioner asks the questions as set out on the Questionnaire (see sample sheet) and notes down the responses.
(The answers will be recorded using a simple key, devised as a group. A 1 will record the answers noted from the first person and the data received by the second by a 2 etc.) This number will be placed into a group/range/type (e.g. they travelled there by coach, or they are male). This will be done so it is possible to see if a lot of people have things in common, or it the results are just completely random.
- After the above is completed the Questioner will thank the respondent for their time.
- If:
- After this time he has gathered data from at least 25 people, then he moves on to his next given task.
-
After this time he has not gathered data from the minimum requirement he will start the random selection method again and repeat the above.
Strengths and Weaknesses of the Questionnaire
Weaknesses
Some of the questioners travelled around in large groups as opposed to doing the survey individually. If they were to do this the number of boys doing the survey in one area will be more concentrated than another e.g. In a place where there would be very few people or tourists.
The date that we visited Betws-Y-Coed would have had an influence on the results. The date we visited the village was 9th October 2001. As this was in the Autumn Season there would have been fewer tourists as the weather in Wales is not going to improve much as to make tourists want to visit the area.
We only surveyed the area for a short period of time. By doing this we received inaccurate data, as if we had done it over a larger period of time e.g. one week our results would have been more accurate as there would have been more data to analyse.
Many people asked to participate refused to co-operate- making it difficult to collect the data. This may have decreased the range as more people welcoming people may have varied our results.
Very few people knew the distance that they had travelled. Time was lost when the Questioner was trying to find out how far they had travelled.
Strengths
Most of the visitors seemed to congregate in one particular area. This helped because the questioner did not lose time walking distances to find people to interview.
Approximately 60 students had interviewed at least 25 people each, creating a great range of results.
The weather was pleasant meaning that more people were outdoors at the time, so the survey was done with greater ease.
We collected our data using numbers-as the person was questioned answers were writes down in number form. Writing down streams of writing would have become tiresome for the Questioner.
We asked if the respondent had previously participated in a questionnaire. By doing so we did not acquire data which had already collected- making our results more accurate
Table of relevant Results from the Questionnaire
Pie Chart for Purpose of Visit
Stacked Area for Transport Used
This chart presents the data for the transport used. It shows that 278 of the respondents questioned travelled there by coach.
Histogram for Distance travelled
Age gender pyramid
Choropleth map for origin
Analysis
Reminder of my Hypothesis:
It was predicted in my Hypothesis that the majority of people visiting Betws-Y-Coed will fall into a general category. It was predicted that the majority of people would be female, around the age of 60 and that they would have travelled there by coach and a maximum distance of 150 miles.
Description
Techniques used:
- Age-Gender Pyramid
- Stacked Area
- Histogram
- Pie-Chart
- Choropleth
The Age-gender Pyramid, which represents the age and gender of the respondents. This technique was chosen to show this data because it represents well the accuracy of the Hypothesis, the data was continuous as each range on both axis relate to each in a direct proportion, so it could and was shown on a continuous chart. This was also used as it enables us to show two pieces of information in one chart.
The chart shows that of all the females that participated in the survey about 30 were over 76 years old, 170 were between the ages of 61-75, 80 were ages 46-60, about 40 were between 31-45, 20 were 16-30 and 15 were aged 15 or younger. For the males that visited Betws-Y-Coed and participated in the survey, the technique shows that about 20 were aged 76+, about 130 were aged 61-75, about 80 were between 46-60, 45 were ages 31-45, about 15 were 16-30 and approximately 10 were aged 15 or younger.
The trend here is that there were more females than males and that the majority of them were in the age range of 61-75, following my Hypothesis.
This particular technique may have improved by a few methods, one of which would have been collecting the exact ages of the respondents. Doing so would have enabled us to produce a curved technique rather than one consisting of bars. But doing so may have offended the respondents.
The Stacked Area- this was used to represent the data showing the different modes of transports used by visitors to the area. This technique was chosen because it was simple, like the data itself. It can be easily represented and analysed with this technique. This data is dis-continuous because the categories on the x-axis do not relate t each other.
This technique shows that approximately 280 people arrived to Betws-Y-Coed by coach, about 240 by car, 70 by bus; nearly 40 by foot, 35 people by train, 5 by bicycle and 20 arrived by other “means”.
The trend is that the majority of people travelled there by car, which does not agree with my Hypothesis.
A histogram was used to represent the distance that the respondents had travelled to get to Betws-Y-Coed. This technique was chose to be used because the values and/or ranges on both axes were directly related to one another so a continuous technique such as a histogram seemed fairly suitable.
The technique shows that about 160 people travelled 51-100 miles; about 150 people travelled 21-50 miles, about 80 people travelled 6-20 miles and about 70 people travelled under 5 miles.
The trend is that the majority of people travelled from over 100 miles and a lot travelled between 21-50 miles and 51-100 miles to get to Betws-Y-Coed, which does reflect some light on my Hypothesis but not accurately enough.
This technique could have been improved by making the range more specific. E.g. Every 5 or 10 miles up to 150miles- as to obtain more accurate results.
The Pie Chart. This was used to represent the data showing why the respondents travelled to the area. The data being collected was dis-continuous as none of the categories were related in any way, and as a pie chart shows dis-continuous data it was chosen for this. Another reason it was used was because that it is rather simple and therefore easier to analyse than most other charts.
This technique shows us that about 80% of the respondents were in Betws-Y-Coed for the purpose of tourism; only 6.8% were there for work, only 5/6% to visit a friend and only 6.8% for other purposes.
This technique could not be improved because it was so simple as was the data.
Hypothesis
I predict that the majority of vehicles travelling through Betws-Y-Coed will be cars with some LGV’s but far fewer. I also predict that the busiest of the three junctions we will be surveying is likely to be Junction B.
Hypothesis Explanation
There will be more cars than any other vehicle because it is the most common form of transport. Although I predict this it differs to what you may expect with regards to my previous chapter. In the Questionnaire Chapter I predicted that the majority of people would be travelling by coach. The reason that I predict more cars in this chapter is because it must be recognised that coaches can carry numbers that several cars could not.
I also predicted that there would be quite a number of LGV’s. The reason for this prediction is that there are likely to be Good’s Vehicles supplying all the shops in the Village. The reason I did not predict there to be many HGV’s is because the roads in the village are far too small for them to travel comfortably on.
Aim
My aim is to prove my hypothesis correct. In order to accomplish this surveys will be carried out in the village of Betws-Y-Coed in the form of Traffic Tallies. These tallies will be designed in class in preparation for the fieldwork. The fieldwork will take place on Tuesday 9th October.
About the Traffic Tally
The traffic tally was previously designed in class, in preparation for use for our visit.
The tallies took place between the hours of 11:00am and 2:00pm on Tuesday 9th October.
The tally sheets were placed on a clipboard and placed in a polystyrene bag as to protect it as a precaution for unwanted weather changes.
Categories that were selected for use on the tally sheet were as follows:
1.car
2.LGV
3.HGV
4.Bikes
5.Coach
6.Other
The designated roads were monitored in turn so that each person monitored a road for 30minutes.
All of the vehicles that passed through any of the monitored roads were recorded with a simple tally system to categorise what type of vehicle they were and the direction that they were going.
The design of the Tally System can be seen on the Sample Tally Chart.
How the Tally Chart was filled in
Junction A
As junction C leads to
a number of small car
parks outside the village
centre there will be fewer
cars passing through this
Junction than Junction
B but more than Junction
A. I predict that this will
be the second busiest of
the three Junctions.
Junction B
As junction C leads to
a number of small car
parks outside the village
centre there will be fewer
cars passing through this
Junction than Junction
B but more than Junction
A. I predict that this will
be the second busiest of
the three Junctions.
Junction C
As junction C leads to
a number of small car
parks outside the village
centre there will be fewer
cars passing through this
Junction than Junction
B but more than Junction
A. I predict that this will
be the second busiest of
the three Junctions.
