In six pages this study design considers statistical assessment techniques such as Chi Square and ANOVA testing applied to an evaluation of gas additive effectiveness. Four sources are cited in the bibliography.
Name of Research Paper File: CC6_KSstatBizGasAdd.rtf
Unformatted Sample Text from the Research Paper:
There has been much attention trained on finding alternatives to fossil fuels over the past two decades, but not all of those involved have financial reasons for wanting to effect
a shift away from dependence on foreign oil. Members of established industry are unlikely to aggressively search for alternatives to the single product that has created some of the
worlds largest businesses. Fuel additives claiming to increase gas mileage have been available for years, but most have proven to be more creative
in marketing than in function. One product, GoMore, appears to hold greater promise for positive results than its predecessors, and a testing agency has determined to test GoMores producers
claims of effectiveness. The purpose here is to identify appropriate statistical tests of data. Design Considerations Method is always important in arriving
at true, non-biased results, but it is of even greater consequence in this problem than in some others. There are many types of drivers and driving situations, and specific
kinds of cars are better suited to some sets of conditions than others. For the study to be effective, the agency will need to begin with vehicles identical in
as many mechanical ways as possible, ensuring that car size, motor size, maintenance level and other factors are similar across all vehicles used in the study.
Following that, the testing agency needs to classify test groups according to how the cars will be tested for fuel use. These are road tests, and
as such, occur over time in actual service. It has long been established that highway driving gains better fuel efficiency than does in-town driving. Any study that does