Rebecca Parker and Kristen Robinson's
EMAT 4680 Data Analysis Project
# of Pupils Per Computer

vs.

Teacher Salary

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Objective:

To study the relationship between the number of pupils per computer in a state and the average teacher salary in the state.

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Hypothesis:

The fewer the number of pupils per computer, the greater the teacher salary.

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State
# Pupils Per Computer
Teacher Salary
1
North Dakota
15
$28,553 
2
Georgia
16
$35,688 
3
Alaska
17
$36,818 
4
Washington
19
$35,103 
5
Iowa
21
$34,920 
6
Utah
21
$29,842 
7
Indiana
22
$40,264 
8
Oregon
22
$38,800 
9
Montana
23
$30,604 
10
New Mexico
23
$29,597 
11
North Carolina
24
$34,340 
12
Nevada
25
$36,419 
13
Maine
31
$29,275 
14
Kentucky
32
$36,803 
15
New York
34
$41,157 
16
Idaho
35
$31,150 
17
Illinois
38
$39,390 
18
Michigan
37
$50,224 
19
Tennessee
38
$35,210 
20
Florida
39
$35,598 
21
Alabama
44
$34,713 
22
New Jersey
42
$38,422 
23
New Hampshire
46
$32,979 
24
Arkansas
47
$33,284 
25
Rhode Island
49
$36,711 
26
California
52
$36,110 
27
Massachusetts
53
$34,076 
28
Delaware
54
$38,272 
29
Ohio
62
$38,833 
30
Mississippi
63
$30,894 
31
Hawaii
74
$28,259 
32
West Virginia
82
$36,616 
33
Louisiana
89
$30,303 
U.S.
35
$36,744 

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Analysis of Data

The hypothesis was found to be incorrect. By the graph, it is obvious that no possible trend line accurately represents the correlation between the data. In fact, there is close to zero correlation between the data. By the figure below, we can see that the correlation coefficient is .0051.
 
 

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Several explanations for the inaccuracy of the hypothesis:
ØThe funding for the computers and the funding for the teacher salaries could come from different parts of the state's education budget.
ØThe schools with a smaller ratio of pupils to computers may spend so much on technology that there is not a great amount of money left for high teacher salaries.

ØThe amount of data may have been too great or too small to form a definite conclusion.

ØBoth the population density and the total population of the state varies greatly from state to state, thus affecting the ratio of students to computers.(Ex.:Georgia vs. Rhode Island)

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Extension:

Explore the correlation between the two variables in private rather than public schools.

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Go To Kristen's Web Page
Go To Rebecca's Web Page