study. Using the same headings as in the summary, write up a detailed, step- by-step procedure of how you will prepare the report. Include data collection forms and anything else that will make the job easy. You might even build the data tables for your final graphs and charts, put in dummy numbers, and get everything looking nice. That way, if you are rushed at the end, you can drop in the data, run the statistics, drop in the results, and the report will be nearly done. Of course, you should be very careful that you adjust the charts and graphs to match the actual data before you deliver the report.
A large statistical study is a major project. For major projects, best practices should be used for time and cost estimation, and also for risk and quality planning. This topic goes beyond this book, but we can recommend another text in the series,Project Management Demystified, by Sid Kemp.
or informal, depending on how your company works and how much the statistical study is going to cost.
As you go for approval, there are some extra items to consider. We have guided you in preparing the plan as if your only goal is to provide a report supporting one set of business decisions. And that may well be best. But you should also look to the future, and ask if you can create additional value while you are doing this statistical study.
. Making the study repeatable.Is it likely that the business will want this information again in the future, perhaps even on a regular schedule, such as quarterly or annually? If so, you can plan things that will make the study easy to repeat, and show the value of reducing the cost of repeating the study in the future.
. Gathering all the data that you can afford.If you are doing a survey, a quasi-experiment, or an experiment, you will probably find that doing it at all is expensive, but getting more data while you do it does not add much to the cost. Getting more data than you think you need has three advantages. If the statistician decides that additional statistical proce- dures are useful for this study, you are more likely to be able to do them. If the business audience thinks of additional questions when they see your report, you may be able to answer them. And if another business audience, such as another department, could use data from the same population, they may be willing to pitch in and pay for part of the study.
. Making the study a model.Even if this exact study will not be repeated on this population in the future, similar studies might be useful for your audience. For example, if this study examines a few new cities to determine if they are viable markets for your company, you may want to set up the plan so that a similar study can be done in different cities in the future.
As you go for approval, you will probably have a sense of whether what you are proposing is about what was expected, or if you discovered that things are going to cost a lot more than your boss would like. If cost seems like it might be a problem, prepare options. For example, you can show the possibility of purchasing data, rather than collecting them, but point out that the data are somewhat out of date and also don’t allow you to run some of the statistical procedures that you want. There is a possibility that all your planning will lead to a decision that the study is too expensive, that it is not worth doing. That is not a bad thing. By doing careful planning, you have saved the company from the mistake of spending too much money.
But we should end on a happy note. In all likelihood, your study will be approved. Why? Because the cost of a statistical study is a lot less than the cost of running a business on guesswork. You are adding real value to the company by preparing this study. And you have planned it well enough that it is likely to be an excellent study, and easy to carry through.
Quiz
1. The1:10:100 ruledemonstrates the importance of. . . (a) Writing clearly
(b) Conducting good statistical analysis (c) Planning
(d) Fixing problems after they occur
2. What information do you need to determine the Plan Objectives?
(a) When is the report due?
(b) What decisions will the information support?
(c) What is the budget?
(d) All of the above
3. Working with a consulting statistician is critical to which phase of planning?
(a) Stating the research questions
(b) Writing up the plan and getting it approved (c) Determining the plan objectives
(d) Planning the statistical report
4. Comparing the cost and time estimates to our budget and delivery date help us determine . . .
(a) The research plan
(b) Stating the research questions (c) The practicality of the study (d) Planning the statistical report
5. The most expensive method of data collection is. . . (a) Using data the company already owns (b) Performing a survey
(c) Performing a quasi-experiment (d) Performing an experiment
6. The best way to plan the data analysis is to use a _______ pass, followed by a _______ pass.
(a) Backward; backward (b) Backward; forward (c) Top-down; bottom-up (d) Bottom-up; top-down
7. The most important aspect of planning a statistical report is to. . . (a) Be as precise as possible
(b) Look at a report from your company (c) Consider the audience
(d) Use as many numbers as possible
8. The first page of the written plan should contain. . . (a) The purpose of the report
(b) The process you will use (c) The cost of the study (d) All of the above
9. Your budget should contain what information?
(a) Costs of man hours and materials to be purchased (b) Costs of man hours only
(c) Costs of materials to be purchased only (d) Costs of preparing the report
10. How can you create additional value of your statistical study?
(a) Make the study repeatable
(b) Gather all the data that you can afford (c) Make the study a model
(d) All of the above
CHAPTER
Getting the Data
Quality data collection means obtaining reliable, valid data at low cost that is suitable for our planned statistical analyses. Happily, a properly planned data collection gives not only higher quality, but usually lower cost as well.
There are three things we need to plan:
. We need to identify the bestsource for our data.
. We need to choosemethods that ensure reliable and valid data.
. We need to choose a researchdesignthat ensures the suitability of our data for our planned analysis.
This chapter will be devoted mostly to considering various sources for our data. We will also discuss proper data collection methods. Research design will be addressed in Part Three.
Stealing Statistics: Pros and Cons
When data are available, either for free or for sale, the data providers usually also provide summary statistics describing the data. If the summary statistics they provide are suitable for our needs, it will save us time on the analysis.
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Some statistics can be calculated from other statistics, even without the detail data. Sometimes, we can just use the summary statistics provided directly.
A big advantage to using someone else’s statistical results is that sometimes the detail data cannot be supplied, for security or privacy reasons. Medical data are a very good example. It is perfectly legal to provide information as to how many American citizens have AIDS, including breakdowns by state and ethnicity. It would be a very different matter to give out their names and addresses.
The two biggest problems in using someone else’s statistics are that we cannot double-check the calculations done by the provider and we cannot calculate any statistical results the provider left out. Also, if the provider made any errors, we will inherit those errors and they will contaminate any further analyses we do using those statistics. If the provider failed to calculate particular statistics we need, there is no way to calculate those statistics without the detail data.
CRITICAL CAUTION Inheriting Errors
Inheriting the errors of others is far more common—and far more costly—than you might think. One study traced small factual errors that got into textbooks and found that they stayed for decades, through several generations of authors.