Transcript scatter plots II

Investigating Scatter Plots
Mr. J. D. Miles
www.JovanMiles.com
[email protected]
Investigating Scatter Plots
Weight Loss Over Time
How shirts affect salary
250
500000
200
400000
Salary
Weight
150
Weight
100
300000
200000
100000
50
0
1
0
2
4
6
8
10
12
Da ys w orke d out pe r month
5
7
100
80
60
40
20
0
0
0.5
1
1.5
2
2.5
3
Time in hours
3.5
9
11
Shirts Owned
How Study Time Affects Grades
120
Overall grade
0
3
4
4.5
5
13
15
17
Investigating Scatter Plots
• Scatter plots are similar to line graphs in that
each graph uses the horizontal ( x ) axis and
vertical ( y ) axis to plot data points.
• Scatter plots are most often used to show
correlations or relationships among data.
Investigating Scatter Plots
• Positive correlations occur when two variables
or values move in the same direction.
 As the number of hours that you study increases
your overall class grade increases
Investigating Scatter Plots – Positive
Correlation
How Study Time Affects Grades
120
Overall grade
100
80
60
40
Study Time
Class Grade
0
55
0.5
61
1
67
1.5
73
2
81
2.5
89
3
91
3.5
93
4
95
4.5
97
20
0
0
0.5
1
1.5
2
2.5
3
Time in hours
3.5
4
4.5
5
Investigating Scatter Plots
• Negative Correlations occur when variables
move in opposite directions
 As the number of days per month that you
exercise increases your actual weight decreases
Investigating Scatter Plots – Negative
Correlation
Work out time
Weight Loss Over Time
250
200
Weight
150
Weight
100
50
0
0
2
4
6
8
10
Days w orked out per month
12
Weight
0
200
0.5
205
1
190
1.5
195
2
180
2.5
190
3
170
3.5
177
4
160
4.5
170
5
150
5.5
168
6
140
6.5
150
7
130
7.5
170
8
120
8.5
130
9
110
9.5
115
10
100
10.5
120
Investigating Scatter Plots
• No correlation exists if there is no noticeable
pattern in the data
 There is no relationship between the number of
shirts someone owns and their annual salary
Investigating Scatter Plots – No
Correlation
How does your wardrobe affect your
salary
number of shirts
owned
80
Salary
60
40
20
0
0
10
20
30
Number of shirts owned
40
50
salary
1
1
2
0
3
50
4
30
5
25
6
17
7
2
8
40
9
8
10
25
11
12
12
7
13
19
14
55
15
71
16
9
Line of Best Fit
• A line of best fit is a line that best represents the
data on a scatter plot.
• A line of best fit may also be called a trend line
since it shows us the trend of the data
 The line may pass through some of the points,
none of the points, or all of the points.
 The purpose of the line of best fit is to show the
overall trend or pattern in the data and to allow
the reader to make predictions about future
trends in the data.
Use the data to create a scatter plot
Total Fat (g)
(X)
Total Calories
(y)
Hamburger
9
260
Cheeseburger
13
320
Quarter Pounder
21
420
Quarter Pounder with Cheese
30
530
Big Mac
31
560
Arch Sandwich Special
31
550
Arch Special with Bacon
34
590
Crispy Chicken
25
500
Fish Fillet
28
560
Grilled Chicken
20
440
Grilled Chicken Light
5
300
Sandwich
Scatter Plot of the Data
Fat Grams and Calories in Food
700
Total Calories
600
500
400
300
200
100
0
0
5
10
15
20
25
Total Fat Grams
30
35
40
Things to remember
• A scatter plot with a positive correlation has X
and Y values that rise together.
• A scatter plot with a negative correlation has X
values that rise as Y values decrease
• A scatter plot with no correlation has no visible
relationship
• The line of best fit is the line that best shows
the trend of the data
Investigating Scatter Plots
Mr. J. D. Miles
www.JovanMiles.com
[email protected]