A traffic safety company publishes reports about motorcycle fatalities and helmet use. the first accompanying data table, the distribution shows the proportion of of injury for motorcycle accidents. The second data table shows the location of injury and fatalities for 2041 riders not wearing a helmet. Complete parts (a) and (b) Click the icon to view the tables. Click the icon to view the chi-square table of critical values.

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Location of Injury    Probability    Frequency
Multiple Locations    0.570         1021
Head      0.310                               855
Neck    0.030                                 35
Thorax    0.060                               81
Abdomen/Lumbar/Spine    0.030    49

 

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What is the test statistic?
x=(Round to three decimal places as needed.)
What is the range of P-values for the test?
The range of P-values for the test is
Based on the results, does the distribution of fatal injuries for riders not wearing a helmet follow the distribution for all other riders at a significance level of a = 0.10?
sufficient evidence that the distribution of fatal injuries for riders not wearing a helmet
the distribution for all riders.
(b) Compare the observed and expected counts for each category. What does this information tell you?
Motorcycle fatalities from
There
occur
frequently for riders not wearing a helmet, while they occur
frequently for all other locations.
Transcribed Image Text:What is the test statistic? x=(Round to three decimal places as needed.) What is the range of P-values for the test? The range of P-values for the test is Based on the results, does the distribution of fatal injuries for riders not wearing a helmet follow the distribution for all other riders at a significance level of a = 0.10? sufficient evidence that the distribution of fatal injuries for riders not wearing a helmet the distribution for all riders. (b) Compare the observed and expected counts for each category. What does this information tell you? Motorcycle fatalities from There occur frequently for riders not wearing a helmet, while they occur frequently for all other locations.
A traffic safety company publishes reports about motorcycle fatalities and helmet use. In the first accompanying data table, the distribution shows the proportion of fa
of injury for motorcycle accidents. The second data table shows the location of injury and fatalities for 2041 riders not wearing a helmet. Complete parts (a) and (b) b
Click the icon to view the tables.
Click the icon to view the chi-square table of critical values.
(a) Does the distribution of fatal injuries for riders not wearing a helmet follow the distribution for all riders? Use a = 0.10 level of significance. What are the null and a
hypotheses?
Ho: The distribution of fatal injuries for riders not wearing a helmet
H₁: The distribution of fatal injuries for riders not wearing a helmet
Compute the expected counts for each fatal injury.
Observed Count
Location of injury
Multiple Locations
Head
Neck
Thorax
Abdomen/Lumbar/Spine
1021
855
35
81
49
C
Expected Count
the same distribution for all other riders.
the same distribution for all other riders.
Transcribed Image Text:A traffic safety company publishes reports about motorcycle fatalities and helmet use. In the first accompanying data table, the distribution shows the proportion of fa of injury for motorcycle accidents. The second data table shows the location of injury and fatalities for 2041 riders not wearing a helmet. Complete parts (a) and (b) b Click the icon to view the tables. Click the icon to view the chi-square table of critical values. (a) Does the distribution of fatal injuries for riders not wearing a helmet follow the distribution for all riders? Use a = 0.10 level of significance. What are the null and a hypotheses? Ho: The distribution of fatal injuries for riders not wearing a helmet H₁: The distribution of fatal injuries for riders not wearing a helmet Compute the expected counts for each fatal injury. Observed Count Location of injury Multiple Locations Head Neck Thorax Abdomen/Lumbar/Spine 1021 855 35 81 49 C Expected Count the same distribution for all other riders. the same distribution for all other riders.
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