For each of the following, determine which property is the independent variable and which is the dependent variable.
1. Carbon dioxide consumption verses sunlight exposure of a plant.
(Sunlight exposure is the independent variable, and carbon dioxide consumption is the dependent variable.)
2. Breathing rate verses the rate oxygen consumption.
(Breathing rate is the independent variable, and the rate of oxygen consumption is the dependent variable.)
3. The rate that sugar dissolves verses the temperature of the coffee.
(The temperature of the coffee is the independent variable, and the rate that the sugar dissolves in the dependent variable.)
4. Pulse rates of athletes and non-athletes before and after exercise.
(The pulse rates are the dependent variable, and the independent variable is before and after exercise.)
5. The pH of tea and cokes with 1, 5, 10, 15 drops of lemon juice added to each one.
(The pH of the tea and cokes is the dependent variable, and the drops of lemon juice is the independent variable.)
1. Graph the following data (Percent of atmospheric gas) as a pie chart: 70% nitrogen, 21% oxygen,
1% argon, 0.1% carbon dioxide, 0.001% water.
2. Graph the following data as data points using excel or google spreadsheets a scatter with data points(only) :
(1,10); (3,15); (5,25); (7,10); (9,30).
3. Graph the following data as a pie graph using excel or google spreadsheets: (20%, 30%, 10%, 40%)
4. Graph the Air Pollution data from the TCEQ with the amount of pollutants.
1. Complete the table with the pollutant data divided into days of the week(SMTWTFS)
2. Construct a bar graph using excel or google spreadsheets with the Texas Commission on Environmental Quality Ozone data. Be sure to label your graph and give it a title.
Use a data above to make a bar graph with wind speed and high temperature for each day of the week.
(1,10); (3,15); (5,25); (7,10); (9,30).
3. Graph the following data as a pie graph using excel or google spreadsheets: (20%, 30%, 10%, 40%)
4. Graph the Air Pollution data from the TCEQ with the amount of pollutants.
1. Complete the table with the pollutant data divided into days of the week(SMTWTFS)
|
Pollutant......
|
Sunday....
|
Monday...
|
Tuesday...
|
Wednesday
|
Thursday..
|
Friday...
|
Saturday...
|
|
Ozone
(O3)
Week
|
29
1
|
34
1
|
25
1
|
20
1
|
19
1
|
17
1
|
20
1
|
|
Ozone
(O3)
Week
|
21
2
|
22
2
|
23
2
|
21
2
|
17
2
|
28
2
|
32
2
|
|
Ozone
(O3)
Week
|
32
3
|
43
3
|
40
3
|
32
3
|
36
3
|
34
3
|
36
3
|
|
Ozone
(O3)
Week
|
41
4
|
25
4
|
20
4
|
14
4
|
24
4
|
19
4
|
21
4
|
|
Ozone
(O3)
Week
|
22
5
|
22
5
|
19
5
|
|
|
|
|
|
Calculate Avg.
|
29
|
29.2 | 25.4 | 21.75 | 24 | 24.5 | 27.25 |
2. Construct a bar graph using excel or google spreadsheets with the Texas Commission on Environmental Quality Ozone data. Be sure to label your graph and give it a title.
|
Environmental...
Conditions
Per Week
|
Sunday...
|
Monday...
|
Tuesday...
|
Wednesday..
|
Thursday...
|
Friday...
|
Saturday...
|
|
Wind
Speed
Week
|
2.9
1
|
3.7
1
|
3.8
1
|
4.0
1
|
1.6
1
|
2.3
1
|
1.6
1
|
|
High Temperature
|
87.3
|
89.2
|
91.2
|
91.3
|
91.7
|
92.4
|
94.1
|
|
Wind
Speed
Week
|
1.3
2
|
2.1
2
|
1.2
2
|
3.8
2
|
1.9
2
|
2.3
2
|
1.2
2
|
|
High Temperature
|
92.8
|
89.5
|
93.9
|
95
|
96.7
|
94.8
|
86.8
|
|
Wind
Speed
Week
|
.8
3
|
1.1
3
|
.9
3
|
.9
3
|
1.0
3
|
1.3
3
|
1.4
3
|
|
High Temperature
|
89.5
|
92.4
|
94.7
|
94.6
|
93.5
|
95.7
|
97.4
|
|
Wind
Speed
Week
|
1.6
4
|
1.9
4
|
2.5
4
|
2.1
4
|
.9
4
|
1.4
4
|
1.8
4
|
|
High Temperature
|
96.8
|
95.1
|
90.3
|
95.2
|
97.1
|
99.5
|
101.4
|
|
Wind
Speed
Week
|
2.6
5
|
1.7
5
|
1.0
5
|
|
|
|
|
|
High Temperature
|
98.6
|
97.2
|
95
|
|
|
|
|
1. Next use both graphs to determine if wind speed or temperature effected the amount of ozone pollution in the atmosphere.
2. What day of the week had the most ozone. What was the high temperatures for those days?
(Monday, 89.2, 89.5, 92.4, 95.1, 97.2)
3. What week had the most wind? What was the ozone during that week?
(Week 1, 23.429)
4. What week has the highest temperatures? What was the ozone that week?
(Week 5, 27.25)
5. Determine which caused an increase or decrease in the ozone levels: day of the week, temperature, or wind speed.
(Wind speed)
6. Why do you think that your answers in #5 had greatest effect on ozone?
(I think wind speed has the greatest effect on ozone because the week that had the highest wind speed also had a very high ozone level even higher than the week that the temperature was its height.)
This lab was specifically designed to teach students about the importance of graphing. Graphing is a way to put large amounts of data in a concise, readable form. It also makes it easier to compare and contrast different sections of data. Some of the easiest programs to use to create graphing charts are Excel 2010 and Google Docs. Excel 2010 provides formats for scatter data plots, bar graphs, pie charts, line graphs, columns, and several others. Pie charts are handy for percentage studies while scatter data plots work well with coordinates. Bar graphs are best for comparing or contrasting data or showing dates with numbers. Graphing is an important tool for analyzing large amounts of facts or statistics and comparing/contrasting it to other information in an easy-to-read format on an understandable chart.
2. What day of the week had the most ozone. What was the high temperatures for those days?
(Monday, 89.2, 89.5, 92.4, 95.1, 97.2)
3. What week had the most wind? What was the ozone during that week?
(Week 1, 23.429)
4. What week has the highest temperatures? What was the ozone that week?
(Week 5, 27.25)
5. Determine which caused an increase or decrease in the ozone levels: day of the week, temperature, or wind speed.
(Wind speed)
6. Why do you think that your answers in #5 had greatest effect on ozone?
(I think wind speed has the greatest effect on ozone because the week that had the highest wind speed also had a very high ozone level even higher than the week that the temperature was its height.)
This lab was specifically designed to teach students about the importance of graphing. Graphing is a way to put large amounts of data in a concise, readable form. It also makes it easier to compare and contrast different sections of data. Some of the easiest programs to use to create graphing charts are Excel 2010 and Google Docs. Excel 2010 provides formats for scatter data plots, bar graphs, pie charts, line graphs, columns, and several others. Pie charts are handy for percentage studies while scatter data plots work well with coordinates. Bar graphs are best for comparing or contrasting data or showing dates with numbers. Graphing is an important tool for analyzing large amounts of facts or statistics and comparing/contrasting it to other information in an easy-to-read format on an understandable chart.
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