Examine quarterly accident data


This assignment requires an amount of computer work and written comment. You may need to seek guidance from your tutor along the way. Do not leave things until too late!! Each question carefully describes what you are required to do so please follow these carefully!

In this assignment you will examine quarterly accident data obtained from a large company that employs up to 18000 people. Each accident costs the company time and money, and the worker usually has considerable pain and suffering. This company has introduced new work procedures in the hope that the numbers of accidents can be reduced and that their safety performance might be improved. The data is contained in the file Accident Data.xls and contains the following columns (variables):

Variable                         Description

ID                            Identification number from original file
Qtr                           Quarter
Accidents                 Number of accidents
Est-EFT                    Estimated number of Full Time Employees
#/1000                    Number of accidents per 1000 Full Time Employees
WDL/Qtr                  Number of Working Days Lost per Quarter
WDL/1000EFT          Number of Working Days Lost per 1000 Full Time Employees

Random Sample: Before you begin your analysis you are required to take a random sample of size 24 from the 38 cases in the file. Use the file Random Sampler Generator.xls to do this. Your tutor will show you how this can be done in EXCEL. Your answers to the assignment tasks below are to be based on your sample of 24 cases. Make sure to keep a safe copy of your sample since you cannot use Random Sampler Generator.xls to reproduce the first sample.

To prepare your data file ready for analysis you must follow the following steps:

1. Use the Random Sampler Generator file to generate a random sample of 24 from the file Accident Data.xls.

2. After you have generated your sample you need to sort your data by the column headed ID - remember to highlight all of your sample data before sorting.

3. You may have noticed that the second column headed Qtr is empty. Fill the second column with the numbers 1 to 24. These numbers represent quarters and because there are 24 of them you have 6 years of quarterly data.

4. Copy your sample file to another spreadsheet for working your assignment. Make sure you save your random sample.

5. Now you are ready to use your sample data to complete the assignment tasks listed below

Provide a printout of the data in your sample, with ID numbers in ascending order.

Assignment Tasks:

1. This company believed that their average number of quarterly accidents was relatively stable at 56 accidents per quarter. For the last three years the company has insisted that all workers wear protective clothing at all times, including hard hats, steel-capped boots, strong gloves, protective glasses, and so on.

Determine the mean, standard deviation and standard error for the last three years of quarterly data. Use this information to carry out a t-test to see if the average number of quarterly accidents for the last three years is significantly less than 56.

2. Obtain a scatter-plot of the quarterly number of accidents vs working days lost WDL per quarter. Think carefully about which variable should go on the vertical axis - remember, it is the independent variable that goes on the horizontal axis (i.e. the x-axis). Make sure you label your axes properly and your graph has an appropriate title. Briefly describe the nature of the relationship between these two variables.

3. Using Tools>Data Analysis in XL carry out a regression analysis on these two variables. Copy the output into your assignment and use it to determine the following:

o Write down the regression equation
o State the R-Square value and the Standard Error and explain what they mean with respect to this data.
o Write down the value of the gradient of the regression line and explain what it means in this case.
o Is the constant or intercept value significant in this case? How do you know this?
o Briefly explain why you think this regression model is, or is not, a good model.

4. Obtain a time series plot of the number of accidents per quarter. Describe the nature of this time series and identify which of the four time series components are present in this case.

Compare the first half of the time series to the second half (i.e. the first three years with the last three years), and briefly describe any differences.

By right clicking on one of the data points, add a trend line to the time series, making sure you include the regression equation and the R-Square value. Interpret the meaning of the slope coefficient in this case and state whether or not this is good for the company.

Use the regression equation to de-trend the data placing the de-trended data in another column. Obtain a time series plot of the de-trended data and explain what it shows.

5. Using information from your analyses write a short concluding paragraph about whether or not the company has been successful in trying to reduce the number of quarterly accidents for its workers.

ID Qtr Accidents Est-EFT #/1000 WDL/Qtr WDL/1000EFT
1
46 15730.2 2.924 5037 320.21
2
46 15588.8 2.951 4972 318.95
3
56 15447.3 3.625 4324 279.92
4
67 15305.8 4.377 5878 384.04
5
78 15246.9 5.116 8387 550.08
6
55 15270.4 3.602 5017 328.54
7
51 15293.9 3.335 5174 338.30
8
56 15317.5 3.656 5209 340.07
9
58 15343.7 3.780 5426 353.63
10
46 15372.5 2.992 3730 242.64
11
65 15401.4 4.220 7342 476.71
12
47 15430.3 3.046 5123 332.01
13
49 15398.8 3.182 4665 302.95
14
61 15306.9 3.985 6890 450.12
15
69 15215.1 4.535 6256 411.17
16
47 15123.2 3.108 4243 280.56
17
48 15048.7 3.190 3197 212.44
18
50 14991.7 3.335 2978 198.64
19
48 14934.7 3.214 3890 260.47
20
44 14877.6 2.957 4510 303.14
21
50 14821.0 3.374 3794 255.99
22
40 14764.7 2.709 3471 235.09
23
48 14708.5 3.263 5134 349.05
24
46 14652.2 3.139 3191 217.78
25
51 14853.8 3.433 3613 243.24
26
46 15313.1 3.004 3899 254.62
27
40 15772.4 2.536 3958 250.94
28
42 16231.8 2.588 2797 172.32
29
36 16505.7 2.181 3224 195.33
30
47 16594.3 2.832 3610 217.54
31
41 16682.9 2.458 3115 186.72
32
39 16771.5 2.325 2417 144.11
33
46 16902.6 2.721 3599 212.93
34
48 17076.2 2.811 2646 154.95
35
41 17249.9 2.377 4582 265.63
36
41 17423.5 2.353 2684 154.04
37
43 17510.3 2.456 3270 186.75
38
39 17510.3 2.227 2090 119.36

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