Question
In: Statistics and Probability
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 relationship appears to be present between two variables.
- Use the least-squares method to predict the number of defects when production rate is 60.
- Interpret the meaning of the regression coefficients in this problem.
- Compute the standard error of the estimate.
- At a significance level of .01 can you conclude that production rate is a good predictor of the number defects?
- Construct a 95% confidence interval for the population slop.
Solutions
orchestra answered 1 year agoRelated Solutions
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...
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. 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...
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...
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...
Zero Defects & On-target: There are two manufacturing philosophies of manufacturing. Zero-defects is primarily practiced by...
Zero Defects & On-target: There are two manufacturing
philosophies of manufacturing. Zero-defects is primarily practiced
by American manufacturers and on-target is generally adopted by
Japanese companies. Taking an example for an assembly, show
how you will choose the target dimensions if you want to
be close to the ideal by one SD, two SDs, and three SDs for both
manufacturing philosophies. You may assume any adequate SD
dimension.
Example: Say the dimension and tolerance given to you is 100 mm...
11. A manufacturing company produced the following number of units in the last 16 days: 27...
11. A manufacturing company produced the following number of
units in the last 16 days: 27 28 27 28 27 25 25 28 26 28 26 28 31
30 27 26 (e) How many classes would you recommend? Explain. (f)
What class interval do you suggest? Explain. (g) What lower limit
would you recommend for the first class? Explain. (h) Organize the
information into a frequency distribution and determine the
relative frequency distribution. You can do this either by hand...
1. You are interested in predicting the final grade of students in a business course. You...
1. You are interested in predicting the final grade of students
in a business course. You collect data on the number of hours
studied and final grade for 8 students. Using the data provided
below, find the predicted linear regression equation. Copy the data
below into an excel spreadsheet, (or you can to this long hand on
notebook paper). You must show all of your
calculations. Take calculations out to the 4th decimal place. Do
not round up or round down....
develop simple linear regression models for predicting sales as a function of the number of each...
develop simple linear regression models for predicting sales as
a function of the number of each type of ad. Compare these results
to a multiple linear regression model using both independent
variables. State each model and explain R- square, significance F
and P-values.
Concert Sales
Thousands of
Thousands of
Sales ($1000)
Radio&TV ads
Newspaper ads
$1,119.00
0
40
$973.00
0
40
$875.00
25
25
$625.00
25
25
$910.00
30
30
$971.00
30
30
$931.00
35
35
$1,177.00
35
35
$882.00...
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