Solutions Manual
Integrated Science 7th Edition By Bill
Tillery , Eldon Enger Solutions Manual
PRINTED PDF | ORIGINAL DIRECTLY FROM THE PUBLISHER | 100%
VERIFIED ANSWERS | DOWNLOAD IMMEDIATELY AFTER THE ORDER
Complete Test bank, All Chapters are included.
For more Test banks, ATI, HESI exams, and more contact us here:
,Name____________________________________________________Section________________Date___________
Experiment 1: Graphing
Invitation to Inquiry
The measurement of a quantity that can have different values at different times is called a variable.
For example, the rate of your heartbeat, the number of times you breathe per minute, and your blood
pressure are all variables because they can have different values at different times. In many situations,
there are relationships that occur between variables. The rate of your breathing, for example,
increases when you begin to exercise, so you could say that the breathing rate is in direct proportion
to exercise up to a certain limit.
Measurements of variables that increase or decrease relative to each other are in direct
proportion will yield a straight line on a graph, and this relationship is said to be direct, or linear.
There are more types of relationships between variables, and most can be identified as producing one
of five basic shapes of graphs. These are identified, left to right, as no relationship, linear, inverse,
square, and square root.
y y y y y
x x x x x
After giving the possibilities some thought, look for relationships that might result in (1) a
direct relationship, then (2) something other than a direct relationship. Make measurements, graph
your data, then decide which of the five shapes the graph resembles. For example, compare your
heartbeat rate before climbing any stair. Then after climbing 10 stairs, 20 stairs, and 30 stairs, what is
the shape of a graph comparing the heartbeat rate and the number of stairs climbed? What does this
mean about the relationship between the number of stairs climbed and your heartbeat?
What other relationships can you find in the lab, outside, or between any two variables in
everyday occurrences? Summarize your findings here:
1
© 2013 by McGraw-Hill Education. This is proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any
manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part.
,Background
Refer to Figure 1.1 for terminology used when discussing a graph, and see Appendix I on
page 391 for a detailed discussion about the terms.
Unit for
y-variable y-axis
Scale for
200 y-variable
Mass (g)
150
Data
points
100 Best fit smooth
line
Scale for
50 x-variable
x-axis
y-variable
name
0
0 50 100 150 200 250
x-variable Volume (cm3 ) Unit for
name x-variable
Figure 1.1
Procedure
1. Position a meterstick vertically on a flat surface, such as a wall or the side of a lab bench. Be sure
the metric scale of the meterstick is on the outside and secure the meterstick to the wall or lab
bench with two strips of masking tape.
2. Drop a ball as close as possible to the meterstick and measure (a) the height dropped, and
(b) the resulting height bounced. Repeat this for three different heights dropped and record all data
in Data Table 1.1 on page 6. In the data table, identify the independent (manipulated) variable
and the dependent (responding) variable.
3. Use the graph paper on page 9 to make a graph of the data in Data Table 1.1, being sure to follow
all the rules of graphing (see Appendix I on page 391 for help). Title the graph, “Single
Measurement Bounce Height.”
2
© 2013 by McGraw-Hill Education. This is proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any
manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part.
, 4. After constructing the graph, but before continuing with this laboratory investigation, answer the
following questions:
(a) What decisions did you have to make about how you conducted the ball-dropping
investigation?
✓ Must measure the height of the ball to the bottom of the ball, not to the top or center.
✓ Larger initial heights are better - more time to react.
✓ Must be sure not to give the ball any initial velocity.
✓ Better to make the height measurements away from the device so you can look almost
horizontally at the height.
(b) Would you obtain the exact same result if you dropped the ball from the same height
several times? Explain.
No, not exactly. Not only do you have to worry about the things mentioned in (a), but the ball
does not bounce the same every time. A different amount of energy will be lost each time.
(c) Did you make a dot-to-dot line connecting the data points on your graph? Why or why
not?
You should try to draw a smooth curve that best represents the data. A dot-to-dot line
assumes that each value is 100 percent correct. This is not possible. A smooth curve tends to
average out the errors.
(d) Could you use your graph to obtain a predictable result for dropping the ball from
different heights? Explain why you could or could not.
The graph should help you predict the bounced height relatively well. It will vary with
different types of balls. In general, your predictions will be within 5-10 percent of the measured
value, with the averaged data being better than the single measurement data.
3
© 2013 by McGraw-Hill Education. This is proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any
manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part.
Integrated Science 7th Edition By Bill
Tillery , Eldon Enger Solutions Manual
PRINTED PDF | ORIGINAL DIRECTLY FROM THE PUBLISHER | 100%
VERIFIED ANSWERS | DOWNLOAD IMMEDIATELY AFTER THE ORDER
Complete Test bank, All Chapters are included.
For more Test banks, ATI, HESI exams, and more contact us here:
,Name____________________________________________________Section________________Date___________
Experiment 1: Graphing
Invitation to Inquiry
The measurement of a quantity that can have different values at different times is called a variable.
For example, the rate of your heartbeat, the number of times you breathe per minute, and your blood
pressure are all variables because they can have different values at different times. In many situations,
there are relationships that occur between variables. The rate of your breathing, for example,
increases when you begin to exercise, so you could say that the breathing rate is in direct proportion
to exercise up to a certain limit.
Measurements of variables that increase or decrease relative to each other are in direct
proportion will yield a straight line on a graph, and this relationship is said to be direct, or linear.
There are more types of relationships between variables, and most can be identified as producing one
of five basic shapes of graphs. These are identified, left to right, as no relationship, linear, inverse,
square, and square root.
y y y y y
x x x x x
After giving the possibilities some thought, look for relationships that might result in (1) a
direct relationship, then (2) something other than a direct relationship. Make measurements, graph
your data, then decide which of the five shapes the graph resembles. For example, compare your
heartbeat rate before climbing any stair. Then after climbing 10 stairs, 20 stairs, and 30 stairs, what is
the shape of a graph comparing the heartbeat rate and the number of stairs climbed? What does this
mean about the relationship between the number of stairs climbed and your heartbeat?
What other relationships can you find in the lab, outside, or between any two variables in
everyday occurrences? Summarize your findings here:
1
© 2013 by McGraw-Hill Education. This is proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any
manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part.
,Background
Refer to Figure 1.1 for terminology used when discussing a graph, and see Appendix I on
page 391 for a detailed discussion about the terms.
Unit for
y-variable y-axis
Scale for
200 y-variable
Mass (g)
150
Data
points
100 Best fit smooth
line
Scale for
50 x-variable
x-axis
y-variable
name
0
0 50 100 150 200 250
x-variable Volume (cm3 ) Unit for
name x-variable
Figure 1.1
Procedure
1. Position a meterstick vertically on a flat surface, such as a wall or the side of a lab bench. Be sure
the metric scale of the meterstick is on the outside and secure the meterstick to the wall or lab
bench with two strips of masking tape.
2. Drop a ball as close as possible to the meterstick and measure (a) the height dropped, and
(b) the resulting height bounced. Repeat this for three different heights dropped and record all data
in Data Table 1.1 on page 6. In the data table, identify the independent (manipulated) variable
and the dependent (responding) variable.
3. Use the graph paper on page 9 to make a graph of the data in Data Table 1.1, being sure to follow
all the rules of graphing (see Appendix I on page 391 for help). Title the graph, “Single
Measurement Bounce Height.”
2
© 2013 by McGraw-Hill Education. This is proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any
manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part.
, 4. After constructing the graph, but before continuing with this laboratory investigation, answer the
following questions:
(a) What decisions did you have to make about how you conducted the ball-dropping
investigation?
✓ Must measure the height of the ball to the bottom of the ball, not to the top or center.
✓ Larger initial heights are better - more time to react.
✓ Must be sure not to give the ball any initial velocity.
✓ Better to make the height measurements away from the device so you can look almost
horizontally at the height.
(b) Would you obtain the exact same result if you dropped the ball from the same height
several times? Explain.
No, not exactly. Not only do you have to worry about the things mentioned in (a), but the ball
does not bounce the same every time. A different amount of energy will be lost each time.
(c) Did you make a dot-to-dot line connecting the data points on your graph? Why or why
not?
You should try to draw a smooth curve that best represents the data. A dot-to-dot line
assumes that each value is 100 percent correct. This is not possible. A smooth curve tends to
average out the errors.
(d) Could you use your graph to obtain a predictable result for dropping the ball from
different heights? Explain why you could or could not.
The graph should help you predict the bounced height relatively well. It will vary with
different types of balls. In general, your predictions will be within 5-10 percent of the measured
value, with the averaged data being better than the single measurement data.
3
© 2013 by McGraw-Hill Education. This is proprietary material solely for authorized instructor use. Not authorized for sale or distribution in any
manner. This document may not be copied, scanned, duplicated, forwarded, distributed, or posted on a website, in whole or part.
