1. CheckPoint
Describe what the difference is between scientific hypotheses, theories, & laws.
Hypotheses are narrow
They are reasonable predictions to answer questions for observed singular events
Theories are broad, but related hypotheses.
A theory is a well tested explanation for patterns observed in nature based upon many related hypotheses.
Theory of evolution = change happens over time
A law describes patterns in nature
A law doesn't need testing or validation anymore
The law of gravity.

2. Graphing (a Crash Course)
Essential Questions:
How do scientists organize data?
What graph is appropriate for a type of data?
How does graphing help us understand scientific questions/problems?

3. Why Graph?
Science is valid mostly because it uses data to support claims.
When performing an experiment, a scientist must be able to record an immense amount of data and process that data into useful information.
This is done by converting raw data into charts or tables.
Data is difficult to see trends, however.
So, the data must be graphed such that it can be interpreted by the public.
Graphs are visual representations of data that make analysis easier.

4. Part 1: Tables and Charts
Tables and charts are created for organizing data from raw data.
Raw data is the numbers that are gathered in experiments.
The chart should show how a trend occurs over several occurrences, (months, trials, categories, etc.) or over time.
Once data is organized, it can be graphed!

5. Variables Recall independent and dependent variables from yesterday.
Independent Variables = those the experimenter changes
Dependent Variables = those that respond to the independent variable.
If you notice, some of the information in a chart depends on the other.
Which information depends on the other; months or temperature?
In this table, temperatures DEPEND on the month. Not the other way around.
We use this information to determine that temperatures are the dependent variable.
In graphing, the dependent variable always goes on the Y axis.

6. Discuss with Partners
Graphs show the relationship between the independent and dependent variables. When you see a graph how do you determine what is the independent variable and what is the dependent variable?

7. Part 2: Graphing Data A) Circle/Pie Graphs
Pie graphs are useful in showing percentages, parts of the whole.
Displays how different categories are represented within a topic area.
Sample: How many land does Asia take up in the world?

8. Part 2: Graphing Data B) Bar Graphs
A bar graph is a way of showing relationships between groups or sets of variables, typically items that are being compared.
Often, used with qualitative data sets.
It contains an x and y axis.
These are 2 lines that meet at a right angle.
It uses a series of columns to display data.
Example, how does the number of farms in 1910 compare with 1990?
Notice:
The x and y axis are always labeled.
The graph has a title.
The bars are vertical.
The numbers on the Y axis are in sequence for an accurate comparison.
Year

9. B) Histogram (Special Bar Graph)
Remember, graphs are usual visual representations of data.
Sometimes it’s useful to see how often certain events happen in data sets.
Histograms give a rough sense of the density of data.
For example, when analyzing airport arrival statistics one could graph the frequency flights arrived certain minutes apart from each other.
The key to histograms is that data must be clumped together into like groups.
Q: (30 sec): Give a 3 minute range to show how close together flights usually land.
A: Flights usually land within 3-5 minutes of each other.

10. Part 2: Graphing Data C) Line Graphs/X-Y Scatter Plots
A line graph shows the best relationship between 2 variables.
Used for tracking changes over time, quantitative data sets, & establishing correlation.
Along the x-axis (horizontal) is the independent variable.
Along the y-axis (vertical) is the dependent variable.
Has one or more lines connecting a series of points.
Notice:
Time is on the x-axis (independent variable)
(time usually is)
Wage is on the y-axis (dependent variable)
Wage and time are in sequence based upon the independent variable.
X & Y-values are laid out in even increments first before data is entered.

11. Relationship Between Variables
Often You will need to plot individual data points.
Even though they don’t connect they do relate to each other.
Best fit lines are drawn in to show the assumed relationship.

12. Relationship Between Variables
The relationship between the variables presented in line graphs is called correlation.
This is why information is put into the line graph format in the first place.
There are three types.
Positive = Positive slope
Negative = Negative slope
No Correlation = No general trend present.
Sometimes the correlation is perfect but most of the time data isn’t perfect…it requires interpretation.
Interpreting the graph is the key to establishing the relationship between the independent and dependent variables.

13. X-Y Scatter Plots & Line Graphs
Positive Correlation.
Negative Correlation.
No Correlation.
Realistic Data and its Correlation.
What does the realistic correlation look like?
What kind of correlation is shown?
Independent Variable
Dependent Variable

14. “TALKS” The basic requirements for any graph.
Title
 Located at the top of the graph
 Includes both variables
 “The effect of [independent variable] on [dependent variable]” A
Axes
 Independent variable is on the X-axis (horizontal)
 Dependent variable is on the Y-axis (vertical) L
Labels
 X-axis is labeled with the independent variable
 Y-axis is labeled with the dependent variable
 Labels on both axes have units in parenthesis following the label (if necessary) K
Key
 Key is included to the side of the graph if more than one data set is included
 Colors, patterns, or shapes clearly distinguish the different bars or lines on the
graph
 Colors, patterns or shapes are clearly identified in a key S
Scale
 Scale and interval on x-axis is appropriate and consistent (MIN/MAX VALUES)
 Scale and interval on y-axis is appropriate and consistent
 Reasonable starting points are used for each axis
The basic requirements for any graph.
Please look at the handout and use this to double check any graph created in an experiment or investigation!
Any questions?

15. Discuss with your group
DRY MIX
What is it (or what can you guess) and what does it mean?
1 minute
D = Dependent variable
R = Responding variable (aka)
Y = y-axis
M = Manipulated variable
I = Independent variable (aka)
X = x-axis
Helps you to remember what variable goes on which axis.

16. Practice
Get into groups.

17. Creating and Interpreting Graphs
Class Practice…
Many people have pets. One survey of pet owners showed the following breakdown of the type of pets owned: 35% dogs; 35% cats; 10% birds; 5% hamsters, gerbils, mice, rats; 5% reptiles; and 10% other. You would use a pie chart for this.
Complete the graph using the survey data. Estimate the angle of each section of your completed circle graph. Use rulers & protractors for neatness. Give your graph a title and label what each section of the graph represents.
What’s the point of the circle graph? Explain how viewing the graph conveys information to the reader more quickly than reading the list of data.

18. 5% hamsters, gerbils, mice, rats; 5% reptiles;
Class Practice…
Many people have pets. One survey of pet owners showed the following breakdown of the type of pets owned: 35% dogs; 35% cats; 10% birds; 5% hamsters, gerbils, mice, rats; 5% reptiles; and 10% other. You would use a pie chart for this.
Complete the graph using the survey data. Estimate the angle of each section of your completed circle graph. Use rulers & protractors for neatness. Give your graph a title and label what each section of the graph represents.
What’s the point of the circle graph? Explain how viewing the graph conveys information to the reader more quickly than reading the list of data.
35% dogs;
35% cats;
10% birds;
5% hamsters, gerbils, mice, rats; 5% reptiles;
10% other.

19. Circle Graph % Of Pets Owned Is there anything wrong with my graph?
Dogs 35%
Cats 35%
Hamsters, gerbils, mice, rats 5%
Reptiles 5%
Other 10%
Birds 10%

20. Constructing a graph
Decide which variable to place along the x and y axis.
Decide on a scale for your graph.
Start by discussing with your group. How do you determine the scale to use for a graph?
Must be as large as possible within the limits of the paper and still include the largest item of data.
Select your scale with ease of locating points, multiples of 1, 2, 5, or 10 are easiest.
Your Turn! Use the back side & complete the graph.

21. Steps in Graphing. Identify variables Determine type of graph
IV on X, DV on Y
Determine type of graph
Line = Trends over time, comparing 2 variables, correlation
Bar = Comparing multiple sets or qualitative data
Circle = Illustrating parts of the whole
Scale graph
Highest value variable/available space  up to useful #
Plot data
Label/Title/Key
Review. Does your graph make sense?

22. Graph the following data
Concentration of Oxygen in Water
Temperature (°C)
Oxygen Concentration in Freshwater (ppm) 1
14.0 10
11.5 15
10.0 20
9.0 25
8.0 30
7.5
When complete, work together to answer these questions.
What type of correlation is displayed in the graph?
What claim (statement that summarizes the data) could you make?
What would predict the oxygen concentration to be at 40°C?

23. Temperature v O2 Concentration Oxygen Concentration (ppm)
DON’T FORGET “TALKS”
Temperature v O2 Concentration
Oxygen Concentration (ppm)
What type of correlation is displayed in the graph?
Negative correlation
What claim (statement that summarizes the data) could you make?
As temperature increases, oxygen decreases.
What would predict the oxygen concentration to be at 40°C?
Probably between 5 & 7ppm.
Temperature °C

24. Plotting 2 Line Graphs at Once
Sometimes it is necessary to overlay two sets of data at the same time to see how they compare.
In this example, scientists want to see which type of water is effected more by temperature; salt or fresh water.
You will use the graph created from the previous example and overlay the new data onto the graph, illustrating both sets of data.
When plotting multiple sets of data on the same graph it’s important to consider ways to make sure the person reading the graph can tell the difference in the data sets (different marks for different sets of data)

25. Graph the following data
Concentration of Oxygen in Water
Temperature (°C)
Oxygen Concentration in Freshwater (ppm)
Oxygen Concentration in Seawater (ppm) 1
14.0
11.0 10
11.5
9.0 15
10.0
8.0 20
7.5 25
7.0 30
6.0
When complete, work together to answer these questions.
What type of correlation is displayed in the graph?
What claim (statement that summarizes the data) could you make?

26. Temperature v O2 Concentration Oxygen Concentration (ppm)
DON’T FORGET “TALKS”
Temperature v O2 Concentration
Oxygen Concentration (ppm)
1. What type of correlation is displayed in the graph?
Negative correlation
2. What claim (statement that summarizes the data) could you make?
As temperature increases, oxygen decreases, but it decreases faster in freshwater than in seawater.
Temperature °C

27. Create A Line Graph (25pts) This is actual made-up data…
Hypothesis:
   Name         Test Grade            Homework Grade Rob                           61                                35 Thomas                    95                                   50 Mark                44                                   5 Wanda                   93                                   50 Judy                    63                                   15 Haydn              80                                   36 Barbara            62                                   16 Karen                  95                                  50 Marilyn    65                                   7 Phil                                   38
Joe
Sheri
Directions: Create a heading for the X-axis and Y-axis & choose a useful scale (you must start from zero). Plot these data points on the graph provided. Draw a best fit line to better illustrate the general trend of the data. Make sure your finished graph is titled.
Which set of datum shows the independent variable? Which shows the dependent variable?
What does this say about the data? Really think about this. Is there a relationship between the X-values and the Y values in general & what is it?
What type of correlation does this represent?
What do you think the hypothesis was for this experiment?

28. Test Grade
Homework Grade