Question
In: Statistics and Probability
The data listed below provides the number of defects produced in a series of panels. a....
The data listed below provides the number of defects produced in a series of panels. a. Construct a C-chart for this process. b. Does the process appear to be in control? Why or why not?
| Panel | Defects / Panel |
| 1 | 2 |
| 2 | 12 |
| 3 | 9 |
| 4 | 13 |
| 5 | 8 |
| 6 | 10 |
| 7 | 11 |
| 8 | 7 |
| 9 | 9 |
| 10 | 10 |
| 11 | 6 |
| 12 | 9 |
| 13 | 13 |
| 14 | 12 |
| 15 | 15 |
| 16 | 4 |
| 17 | 9 |
| 18 | 10 |
| 19 | 5 |
| 20 | 6 |
| 21 | 10 |
| 22 | 19 |
| 23 | 8 |
| 24 | 8 |
| 25 | 5 |
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Expert Solution
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orchestra answered 3 years agoRelated Solutions
The data in the worksheet provides the number of defects produced in a series of panels....
The data in the worksheet provides the number of defects
produced in a series of panels. a. Construct a C-chart for this
process. b. Does the process appear to be in control? Why or why
not?
Panel
Defects / Panel
1
2
2
12
3
9
4
13
5
8
6
10
7
11
8
7
9
9
10
10
11
6
12
9
13
13
14
12
15
15
16
4
17
9
18
10
19
5
20
6...
A manufacturing company is interested in predicting the number of defects that will be produced each...
A manufacturing company is interested in predicting the number
of defects that will be produced each hour on the assembly line.
The managers believe that there is a relationship between the
defect rate and the production rate per hour. The managers believe
that they can use production rate to predict the number of defects.
The following data were collected for 10 randomly selected
hours.
Defects (Y)
Production rate per hour(X)
2
40
3
45
1
35
2
37
3
40...
A manufacturing company is interested in predicting the number of defects that will be produced each...
A manufacturing company is interested in predicting the number
of defects that will be produced each hour on the assembly line.
The managers believe that there is a relationship between the
defect rate and the production rate per hour. The managers believe
that they can use production rate (X) to predict the number of
defects (Y). The following data were collected for 4 randomly
selected hours.
Defects (Y)
Production Rate Per Hour (X)
20
400
30
450
10
350
20...
1. A manufacturing company is interested in predicting the number of defects that will be produced each...
1. A manufacturing company is interested in
predicting the number of defects that will be produced each hour on
the assembly line. The managers believe that there is a
relationship between the defect rate and the production rate per
hour. The managers believe that they can use production
rate to predict the number of defects. The
following data were collected for 7 randomly selected hours.
Defects Production
rate/h
2 40
3 45
1 20
3 40
5 50
4 30
6 50
Set up a scatter diagram, and discuss what if any...
1. A manufacturing company is interested in predicting the number of defects that will be produced each...
1. A manufacturing company is interested in
predicting the number of defects that will be produced each hour on
the assembly line. The managers believe that there is a
relationship between the defect rate and the production rate per
hour. The managers believe that they can use production
rate to predict the number of defects. The
following data were collected for 7 randomly selected hours.
Defects Production
rate/h
2 40
3 45
1 20
3 40
5 50
4 30
6 50
Set up a scatter diagram, and discuss what if any...
1. T F The number of defects on a product produced by a process is distributed...
1. T F The number of defects on a product produced by a process
is distributed as a Poisson distribution.
2. T F For large binomially distributed populations and small
samples you can use sampling without replacement
3. T F Given a triangular distribution with minimum 2, maximum 8
and mode 7, the probability of being smaller than 7 is greater than
60%
4. T F The hypergeometric distribution describes sampling
without replacement
5. T F The relative frequency of...
Listed below are the data for a local radio station. This shows the number of weekly...
Listed below are the data for a local radio station. This shows
the number of weekly radio advertisements and the projected weekly
sales resulting (adjusted by industry).
Weekly Radio Spots
Sales ($100s)
4
75
10
85
2
62
6
81
8
81
2
57
10
95
6
72
8
89
4
69
Show the data in a scatterplot, to demonstrate the relationship
between the two variables.
Compute and interpret the correlation coefficient.
Listed below are the data for a local radio station. This shows the number of weekly...
Listed below are the data for a local radio station. This shows
the number of weekly radio advertisements and the projected weekly
sales resulting (adjusted by industry). Weekly Radio Spots
Sales
Weekly Radio Spots
Sales ($100s)
4
75
10
85
2
62
6
81
8
81
2
57
10
95
6
72
8
89
4
69
a. Show the data in a scatterplot, to demonstrate the
relationship between the two variables.
b. Compute and interpret the correlation coefficient.
Use the probability distribution to complete parts (a) and (b) below. The number of defects per...
Use the probability distribution to complete parts (a) and (b)
below. The number of defects per 1000 machine parts inspected
Defects 0 1 2 3 4 5 Probability 0.261 0.301 0.242 0.133 0.045 0.018
(a) Find the mean, variance, and standard deviation of the
probability distribution. The mean is:
Use the probability distribution to complete parts (a) and (b) below. The number of defects per...
Use the probability distribution to complete parts (a) and (b)
below. The number of defects per 1000 machine parts inspected
Defects 0 1 2 3 4 5
Probability 0.262 0.291 0.240 0.151 0.037 0.019
(a) Find the mean, variance, and standard deviation of the
probability distribution.
The mean is
nothing.
(Round to one decimal place as needed.)
The variance is
nothing.
(Round to one decimal place as needed.)
The standard deviation is
nothing.
(Round to one decimal place as needed.)...
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