Upcoming SlideShare
×

# Data Interpretation

1,932 views

Published on

Published in: Technology
2 Likes
Statistics
Notes
• Full Name
Comment goes here.

Are you sure you want to Yes No
• Be the first to comment

Views
Total views
1,932
On SlideShare
0
From Embeds
0
Number of Embeds
108
Actions
Shares
0
32
0
Likes
2
Embeds 0
No embeds

No notes for slide

### Data Interpretation

1. 1. Data Interpretation This is where the collected data is explained and linked back to the original idea.
2. 2. Mark scheme: <ul><li>Level 1 : Brief description of the results / basic reasons for the results </li></ul><ul><li>Level 2 : Valid statements about the results. Attempts are made to analyse (data referred to). Conclusions are made. </li></ul><ul><li>Level 3 : Detailed analysis of the material. Data is referred to specifically. Links are made between different data sets and conclusions relate to purpose of enquiry. </li></ul>
3. 3. The key parts to this section are: <ul><li>Describing the data – what does it show? </li></ul><ul><li>Explaining or suggesting reasons for the data – why does it show this? </li></ul><ul><li>Drawing out links between different data sets and linking to your title....... </li></ul>
4. 4. Before you start..
5. 5. Now, start to write your analysis... <ul><li>1. Begin, by making the simple and straightforward points about each graph... </li></ul><ul><li>Begin by asking, “what does it show?” </li></ul><ul><li>Pick out the numbers which support your statements (could be largest / smallest / greatest change) </li></ul>
6. 6. Example:
7. 7. Next: <ul><li>Add more detail and try and explain. </li></ul><ul><li>For each graph, ask and answer the question, “Why is it like this?” </li></ul><ul><li>For example: </li></ul>
8. 8. .......
9. 9. Extending the analysis (Level 3) <ul><li>Try and identify similarities , differences , patterns , links and relationships . </li></ul><ul><li>Look at your data (different graphs) and ask yourself.... </li></ul><ul><li>How are they different? </li></ul><ul><li>In what ways are they the same? </li></ul><ul><li>Why do these differences / similarities exist? </li></ul>
10. 10. For example: