Difference between revisions of "MU FUYAO Questions-answer"
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− | <td><b> 1. | + | <td><b> 1.Year 1998---2007 </b> |
<br>There are some measures having value of 0, I can’t decide whether the measurement is 0 or didn’t have measure. So, I regard it as missing value and delete. | <br>There are some measures having value of 0, I can’t decide whether the measurement is 0 or didn’t have measure. So, I regard it as missing value and delete. | ||
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− | <td>[[File: | + | <td>[[File:Year1998.png|500px|center]]</td> |
+ | </tr> | ||
+ | |||
+ | <tr> | ||
+ | <td><b> 1.Year 2008---2016 </b> | ||
+ | <br>There are some measures having value of 0, I can’t decide whether the measurement is 0 or didn’t have measure. So, I regard it as missing value and delete. | ||
+ | |||
+ | There are some strange values in this dataset. For same location, same time and same measure, but there are different values. I think it’s repetitive value. So, I get average of them. | ||
+ | |||
+ | </td> | ||
+ | <td>[[File:Year2008.png|500px|center]]</td> | ||
+ | </tr> | ||
+ | </table> | ||
+ | |||
+ | =Question 2= | ||
+ | What anomalies do you find in the waterway samples dataset? How do these affect your analysis of potential problems to the environment? Is the Hydrology Department collecting sufficient data to understand the comprehensive situation across the Preserve? What changes would you propose to make in the sampling approach to best understand the situation? | ||
+ | |||
+ | <table> | ||
+ | <table border='1'> | ||
+ | <tr> | ||
+ | <th>Anomalies</th> | ||
+ | <th>Graph</th> | ||
+ | </tr> | ||
+ | <tr> | ||
+ | <td><b> 1.Water temperature </b> | ||
+ | <br>Water temperature went high trend from 2009. And from graph we can see temperature have seasonal patterns, it lead to dissolved oxygen have seasonal patterns. When temperature goes higher, dissolved oxygen goes down. They two have negative relationships | ||
+ | |||
+ | </td> | ||
+ | <td>[[File:Water-temperature.png|400px|center]] | ||
+ | [[File:Dissolved-water.png|400px|center]]</td> | ||
+ | </tr> | ||
+ | |||
+ | <tr> | ||
+ | <td><b> 2.Iron </b> | ||
+ | <br> Quantity of Iron had an extremely increase in 2003 Q3. And it much more higher than every other years and quarters. There must be some uncommon events in that quarter or its sample datas have something wrong | ||
+ | |||
+ | </td> | ||
+ | <td>[[File:Iron.png|400px|center]]</td> | ||
+ | </tr> | ||
+ | </table> | ||
+ | |||
+ | =Question 3= | ||
+ | After reviewing the data, do any of your findings cause particular concern for the Pipit or other wildlife? Would you suggest any changes in the sampling strategy to better understand the waterways situation in the Preserve? | ||
− | + | <table> | |
+ | <table border='1'> | ||
+ | <tr> | ||
+ | <th>Year</th> | ||
+ | <th>Graph</th> | ||
+ | </tr> | ||
+ | <tr> | ||
+ | <td><b> 1.Year1998 </b> | ||
+ | <br>For year 1998, though most of location were polluted, but the value of pollution is low. And pollution were concerned in north-east of the map. For south-west area, there are few pollutions. Though there might be probabilities there were no testing in south-west area in year 1998, but the most highest probabilities for this result is this area is clean in year 1998 | ||
+ | </td> | ||
+ | <td>[[File:1998.png|500px|center]]</td> | ||
+ | </tr> | ||
+ | |||
+ | <tr> | ||
+ | <td><b> 2.Year2016 </b> | ||
+ | <br> From the graph we can see, compared to year 1998, all of locations have pollutions in year 2016. And value of pollutions is much higher than year 1998. In my opinion, wildlife in there area suffered from pollutions these years and their habitats facing pollutions. | ||
+ | |||
+ | </td> | ||
+ | <td>[[File:2016_mu.png|500px|center]]</td> | ||
</tr> | </tr> | ||
</table> | </table> | ||
+ | |||
+ | All locations are polluted now. And we have 10 monitoring locations now. But each of them are responsible for quite big area. If we want to find some area are less polluted, we need to add monitoring locations. Each of them monitor little area than now. And we can collect data with higher accuracy. It's will provide us better idea for how to protect wildlife in these area. |
Latest revision as of 14:05, 21 July 2018
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Question 1
Characterize the past and most recent situation with respect to chemical contamination in the Boonsong Lekagul waterways. Do you see any trends of possible interest in this investigation?
Statement | Graph |
---|---|
1.Year 1998---2007
There are some strange values in this dataset. For same location, same time and same measure, but there are different values. I think it’s repetitive value. So, I get average of them. |
|
1.Year 2008---2016
There are some strange values in this dataset. For same location, same time and same measure, but there are different values. I think it’s repetitive value. So, I get average of them. |
Question 2
What anomalies do you find in the waterway samples dataset? How do these affect your analysis of potential problems to the environment? Is the Hydrology Department collecting sufficient data to understand the comprehensive situation across the Preserve? What changes would you propose to make in the sampling approach to best understand the situation?
Anomalies | Graph |
---|---|
1.Water temperature
|
|
2.Iron
|
Question 3
After reviewing the data, do any of your findings cause particular concern for the Pipit or other wildlife? Would you suggest any changes in the sampling strategy to better understand the waterways situation in the Preserve?
Year | Graph |
---|---|
1.Year1998
|
|
2.Year2016
|
All locations are polluted now. And we have 10 monitoring locations now. But each of them are responsible for quite big area. If we want to find some area are less polluted, we need to add monitoring locations. Each of them monitor little area than now. And we can collect data with higher accuracy. It's will provide us better idea for how to protect wildlife in these area.