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Posted: March 4th, 2014

Application of Statistics lab report

Industrial Engineering 203

Winter 2013 – 14

Caliente Study Raw Data

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Assignment Objectives:

  1. Practice entering data into Minitab.
  2. Practice applying basic terminology to the Caliente experiment from Week 9.
  3. Practice running basic statistics on data (i.e. mean, median, standard deviation, etc)
  4. Practice creating graphs for data (i.e. histogram, boxplot, etc)
  5. Practice running (and analyzing) within and between subjects ANOVA

Step 1:

Remember the Caliente Experiment conducted in lab during week 9.  The data has been entered into two tables (i.e. one table for the heat data and one table for the taste data).  Take this raw data and enter the data into Minitab.  Use the meet Minitab document for assistance.

Step 2:

Run basic statistics on the data.

  1. Identify your hypotheses – the null, along with your alternate.
    1. Mean, median, standard deviation, etc.
    2. Explain what the output means – what is it telling you about the data?
  2. Create graphs that you believe will best illustrate the data
    1. Histogram, boxplot, etc.
    2. Explain what the diagram is telling you about the data

i.    Remember skewedness, etc.

  1. In a MS Word document you should include the following:
    1. Introduction
    2. Methodology (explanation/description of the experiment conducted… include Hypotheses here, along with explanation of Independent and Dependent variable(s))
    3. Results (where you show any graphs, charts, tables, etc.)
    4. Discussion (interpret/explain the results obtained from Minitab)
    5. Conclusion

 

 

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Caliente Studies: Hot Sauce Heat

Subject

Hot Sauce 1

Hot Sauce 2

Hot Sauce 3

Hot Sauce 4

Gender

Age

Year in School

GPA

Ethnicity

Place Born

1

3

4

1

2

M

21

Sr

3.1

India

2

1

3

2

1

F

22

Jr

3.0

New Berlin, WI

3

1

3

2

2

M

19

So

2.0

Waconia, MN

4

3

5

1

4

M

20

So

2.3

Kuwait City, Kuwait

5

2

5

1

1

F

31

Jr

2.9

West Allis, WI

6

4

5

4

1

F

20

So

3.6

Whitewater, WI

7

4

4

1

3

F

21

Jr

3.2

Cedar Rapids, IA

8

1

3

1

2

M

19

So

2.9

Milwaukee, WI

9

1

5

1

1

M

19

So

3.2

Milwaukee, WI

10

1

3

2

1

M

19

So

2.4

Milwaukee, WI

11

1

4

1

1

M

20

So

3.5

Milwaukee, WI

12

4

5

2

4

M

21

Sr

2.5

Milwaukee, WI

13

4

6

5

1

M

19

So

3.0

Milwaukee, WI

14

3

6

4

4

F

19

So

3.1

Plainfield, IL

15

1

4

2

3

F

19

So

2.8

Chicago, IL

16

2

4

2

1

F

20

So

3.7

Hartland, WI

17

3

6

5

5

M

22

Jr

Jeddah Saudi Arabia

18

1

2

1

1

M

22

Jr

2.8

Calcutta, WB, India

19

5

4

4

3

M

18

Fr

3.9

Elgin, IL

20

1

4

1

1

M

21

So

3.6

Jeddah, Saudi Arabia

21

5

7

3

4

F

19

So

3.4

Cudahy, WI

22

1

5

3

3

M

21

Jr

3.8

Stacy, MN

23

5

7

3

4

F

20

So

2.7

West Bend, WI

24

6

6

5

4

F

20

Jr

2.8

Kenosha, WI

25

1

4

2

2

M

19

So

3.8

Sturgeon Bay, WI

26

3

7

4

5

M

22

Sr

2.9

Milwaukee, WI

27

4

6

4

2

M

21

Jr

2.5

Wisconsin Rapids, WI

28

4

5

1

2

F

25

So

3.3

Mukwonago, WI

29

4

7

2

3

F

21

Jr

2.7

Franklin, WI

30

1

2

1

1

M

20

Jr

2.4

Romeoville, IL

31

1

3

1

1

F

20

Jr

2.5

Milwaukee, WI

32

2

3

2

1

F

21

Sr

2.9

Menomonie, WI

 

 

 

 

Caliente Studies: Taste

Subject

Hot Sauce 1

Hot Sauce 2

Hot Sauce 3

Hot Sauce 4

Gender

Age

Year in School

GPA

Ethnicity

Place Born

1

4

6

2

5

M

21

Sr

3.1

India

2

7

5

7

7

F

22

Jr

3.0

New Berlin, WI

3

4

5

6

5

M

19

So

2.0

Waconia, MN

4

6

3

1

5

M

20

So

2.3

Kuwait City, Kuwait

5

2

5

1

4

F

31

Jr

2.9

West Allis, WI

6

6

3

1

6

F

20

So

3.6

Whitewater, WI

7

4

2

2

2

F

21

Jr

3.2

Cedar Rapids, IA

8

3

7

7

5

M

19

So

2.9

Milwaukee, WI

9

3

3

3

5

M

19

So

3.2

Milwaukee, WI

10

7

6

7

6

M

19

So

2.4

Milwaukee, WI

11

5

5

7

4

M

20

So

3.5

Milwaukee, WI

12

6

3

5

4

M

21

Sr

2.5

Milwaukee, WI

13

5

4

6

7

M

19

So

3.0

Milwaukee, WI

14

5

3

4

4

F

19

So

3.1

Plainfield, IL

15

6

7

6

7

F

19

So

2.8

Chicago, IL

16

5

4

3

4

F

20

So

3.7

Hartland, WI

17

6

4

2

3

M

22

Jr

Jeddah Saudi Arabia

18

2

3

4

4

M

22

Jr

2.8

Calcutta, WB, India

19

3

3

2

4

M

18

Fr

3.9

Elgin, IL

20

5

3

5

3

M

21

So

3.6

Jeddah, Saudi Arabia

21

1

1

2

2

F

19

So

3.4

Cudahy, WI

22

2

3

4

6

M

21

Jr

3.8

Stacy, MN

23

3

2

4

3

F

20

So

2.7

West Bend, WI

24

3

3

3

5

F

20

Jr

2.8

Kenosha, WI

25

3

3

6

4

M

19

So

3.8

Sturgeon Bay, WI

26

6

2

5

3

M

22

Sr

2.9

Milwaukee, WI

27

4

1

5

3

M

21

Jr

2.5

Wisconsin Rapids, WI

28

7

6

6

7

F

25

So

3.3

Mukwonago, WI

29

5

5

4

7

F

21

Jr

2.7

Franklin, WI

30

1

3

7

6

M

20

Jr

2.4

Romeoville, IL

31

6

1

5

4

F

20

Jr

2.5

Milwaukee, WI

32

7

5

7

7

F

21

Sr

2.9

Menomonie, WI

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