The biggest safety concern for bicyclists is making sure they are visible to other motorists. wearing a helmet and protective pads. following the specific traffic laws for bikes. making sure the bike fits them properly.
Added by Jenny Z.
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Studies show that 9 out of 10 bicycle riders wear helmets. If 400 bicycle riders are randomly observed, you should expect that there would be an 80% chance that at least how many would be wearing helmets?
Qudsiya A.
The National Highway Traffic Safety Administration publishes reports about motorcycle fatalities and helmet use. The distribution shows the proportion of fatalities by location of injury for motorcycle accidents. $$\begin{array}{lccccc}\begin{array}{l}\text { Location } \\\text { of injury }\end{array} & \begin{array}{c}\text { Multiple } \\\text { Locations }\end{array} & \text { Head } & \text { Neck } & \begin{array}{c}\text { Abdomen/ } \\\text { Thorax }\end{array} & \begin{array}{c}\text { Lumbar/Spine } \\0.03\end{array} \\\hline \text { Proportion } & 0.57 & 0.31 & 0.03 & 0.06 & 0.03\end{array}$$ The following data show the location of injury and fatalities for 2068 riders not wearing a helmet. $$\begin{array}{lccccc}\text { Location } & \text { Multiple } & & & & \text { Abdomen/ } \\\text { of injury } & \text { Locations }& \text { Head } & \text { Neck } & \text { Thorax } & \text {Lumbar/Spine } \\\hline \text { Number } & 1036 & 864 & 38 & 83 & 47\end{array}$$ (a) Does the distribution of fatal injuries for riders not wearing a helmet follow the distribution for all riders? Use the $\alpha=0.05$ level of significance. (b) Compare the observed and expected counts for each category. What does this information tell you?
Inference on Categorical Data
Goodness-of-Fit Test
The National Highway Traffic Safety Administration publishes reports about motorcycle fatalities and helmet use. The distribution shows the proportion of fatalities by location of injury for motorcycle accidents. $$ \begin{array}{lccccc} \hline \begin{array}{l} \text { Location } \\ \text { of injury } \end{array} & \begin{array}{l} \text { Multiple } \\ \text { Locations } \end{array} & \text { Head } & \text { Neck } & \text { Thorax } & \begin{array}{l} \text { Abdomen/ } \\ \text { Lumbar/Spine } \end{array} \\ \hline \text { Proportion } & 0.57 & 0.31 & 0.03 & 0.06 & 0.03 \\ \hline \end{array} $$ The following data show the location of injury and number of fatalities for 2068 riders not wearing a helmet. $$ \begin{array}{lccccc} \hline \begin{array}{c} \text { Location } \\ \text { of injury } \end{array} & \begin{array}{l} \text { Multiple } \\ \text { Locations } \end{array} & \text { Head } & \text { Neck } & \text { Thorax } & \begin{array}{l} \text { Abdomen/ } \\ \text { Lumbar/Spine } \end{array} \\ \hline \text { Number } & 1036 & 864 & 38 & 83 & 47 \\ \hline \end{array} $$ (a) Does the distribution of fatal injuries for riders not wearing a helmet follow the distribution for all riders? Use the $\alpha=0.05$ level of significance. (b) Compare the observed and expected counts for each category. What does this information tell you?
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