Presentation on theme: "How to write your Geography coursework analysis Learning Objective: Know what an analysis is To understand what makes an good analysis Practice analysing."— Presentation transcript:
How to write your Geography coursework analysis Learning Objective: Know what an analysis is To understand what makes an good analysis Practice analysing data Peer assessment
Mock analysis Task question: to delimit the area of your chosen urban area’s CBD. Land use - there will be more shops, services and offices in the CBD compared with the outer areas where there will be mostly residential areas. Traffic count – there will be more traffic in the CBD as people will want to get there. Pedestrian count – there will be more pedestrians in the CBD than the outer areas this is because people want to come here to use the shops and public facilities. Building height – there will be taller buildings in the CBD as the land is very expensive here.
What could we say about these 3 bits of information together?
Language for analysis Therefore….. This shows that….. This may be explained by….. This indicates that….. This was expected… Because….. However…… This suggests that…. In comparison to…..
Peer assessment of an analysis Task question: to delimit the area of your chosen urban area’s CBD. Land use - there will be more shops, services and offices in the CBD compared with the outer areas where there will be mostly residential areas. Traffic count – there will be more traffic in the CBD as people will want to get there. Pedestrian count – there will be more pedestrians in the CBD than the outer areas this is because people want to come here to use the shops and public facilities. Building height – there will be taller buildings in the CBD as the land is very expensive here.
What did you give them and why? What grade I have given the work and why….. What I think they have done to improve this analysis …. What I have learnt from this for my own analysis…
What Edexcel said…. The data is described in some detail and there are a number of analytical as well as descriptive comments. There are several attempts to draw together the main findings and to delimit the CBD of the chosen settlement. The conclusions drawn return to the task question and the student makes a number of valid suggestions to help substantiate the conclusions. However, the lack of analytical comments in some sections of the analysis prevents this work from reaching the top of Level 3. 8 marks
Example analysis: How Did the Building Height Vary Along the Transect?
How Did the Building Height Vary Along the Transect? As we travelled along the transect from McKinney into the outskirts of the area, the building height seems to decrease as shown by figure 12. For instance, at McKinney, the average building height is shown to be around 7.25, and at Leeland, it was 7. However, at Gray, this average decreases to 3.5, and then to 2.5 at Elgin, and at Hermann the average building height at the intersection was about 1.25 floors per building. However, there seemed to be 1 anomaly in this general trend along the transect: Wheeler, which had an average building height of only 1. The numbers 1.25, and 1 are quite similar, and it has to be taken into account that this data was only collected based on four buildings along the entire street, which may have resulted in accurate or misrepresentative results. Why Did Building Height Vary Along the Transect in this Way? The general trend in a decreasing building height along the transect can be explained by the increase in land prices from the outskirts into the CBD. This can be explained by the Bid Rent theory in figure 1, which shows that demand for land in the CBD is greatest, and so the prices are also greatest. This means that rather than building outwards, businesses try to buy the minimal amount of land possible, and so they grow upwards. This suggests that the way land is used along the transect (i.e. how sparingly) varies primarily due to the variation in land prices along the transect. What further Primary Data can Be Used to Support This? The variation in building height along the transect can be explained by the pedestrian count shown in figure 13, which shows that pedestrian count is greatest in the CBD. Because pedestrian count is greatest here, the demand for the land would also be greatest, because the retail shops in this area rely on pedestrians to maintain their business. It is this demand that in creases land prices, therefore limiting the amount of land companies are willing to buy, and so too the number of floors they will need to provide in order to properly deliver all of their merchandise. This theory is further proved by the primary data collected on Urban Density in figure 26. The urban density is most effectively shown by the pictures on the graph, which show that as we go further from the CBD, the open space also increases. This shows that smaller businesses (i.e. local museums etc. which we saw between Wheeler and Hermann), are able to invest in spare land to upkeep the environmental quality, and can afford to grow outwards (taking up more land), rather than up, resulting in a greater number of floors.
Now write your own using this data….. How does the pedestrian count vary along the transect?
Practice analysis Sub question How does environmental quality vary along the transect? Describe what the data shows (use figures from the graph) Explain why it may show this (what other data my you have to back this up) Does this link to theory Make sure you refer to figure numbers
Use a combination of data to answer each sub question…..
How did Environmental Quality Vary Along the Transect? According to figure 28, and 29, the General Environmental Quality was greatest at Hermann, then at McKinney. It was least at Wheeler. Traffic was worst at Leeland, and the open spaces were in the most quantity at Hermann, which contributes to the environmental quality of the area. In my opinion, the environmental quality dipped at Wheeler and went up again at Hermann, according the field sketches shown by figures 19-25, and the digital photographs in figure 26. Aside from these trends there seems to be little correlation, or general trend in environmental quality along the CBD. Why Did Environmental Quality vary Along the Transect in this Way? The environmental quality is likely to be greatest at McKinney because of the types of businesses that have invested in land in this Area, typically it would be the very wealthy retail shops that are able to afford this land. Because they are wealthy, they would be able to invest more money in the surroundings, than the smaller business in the outskirts, which must occupy cheaper land. Moreover, because these businesses rely on Customer appeal, they try to attract pedestrians into the area. By providing a good environmental quality, more pedestrians will be drawn to the shop. Also, the reason that places such as Hermann may have had to such a high environmental quality, is primarily because Hermann is the main museum district of Houston, so like the retail shops, they rely on the environmental quality of the nature around them to attract customers. It is also one of the few parks provided to those who live in Houston to attract customers to their park, the environmental quality must be of a higher standard than, for instance that at wheeler, which is occupied mostly by fast-food restaurants. Lastly, the reason why there may not have been any other prominent trends in the environmental quality along the transect, is due to the nature of the data. Environmental quality is very subjective, and is not based on any numerical data, but rather the opinions of the two people that recorded data. This may not accurately represent the environmental quality of each site.
Your checklist for analysis Analysis and conclusions Done? I have described what the data shows I have explained why the data shows this I have linked my explanations to geographical theory I have linked my results to the sub questions I have made links between the various results I have referred to the figure numbers when describing the data I have described anomalies in the data I have given an overall conclusion to the study and answered the initial questions