Question

In: Statistics and Probability

A particular report from 2004 classified 721 fatal bicycle accidents according to the month in which...

A particular report from 2004 classified 721 fatal bicycle accidents according to the month in which the accident occurred, resulting in the accompanying table.

Month Number of Month Accidents
January 37
February 33
March 44
April 60
May 78
June 73
July 97
August 85
September 63
October 67
November 43
December 41

(a) Use the given data to test the null hypothesis H0: ?1 = 1/12, ?2 = 1/12, . . . , ?12 = 1/12, where ?1 is the proportion of fatal bicycle accidents that occur in January, ?2 is the proportion for February, and so on. Use a significance level of 0.01. (Use 2 decimal places.)
?2 =  

(b) The null hypothesis in Part (a) specifies that fatal accidents were equally likely to occur in any of the 12 months. But not all months have the same number of days. Test the hypotheses proposed in H0: ?4 = ?6 = ?9 = ?11 =

30
366

? 0.082, ?2 =

29
366

? 0.079, ?1 = ?3 = ?5 = ?7 = ?8 = ?10 = ?12 =

31
366

? 0.085 using a 0.05 significance level. (Use 2 decimal places.)
?2 =  

Solutions

Expert Solution

(a) =sum(O-E)2/E=78.37 with k-1=12-1=11 df

critical chi-square(0.05,11)=19.67 is less than calucted chi-square, so we reject null hypothesis and conclude that each months are not equal

Month Oberved(O) Expected(E) (O-E) (O-E)2/E
January 37 60.08333333 -23.0833 8.868354
February 33 60.08333333 -27.0833 12.20816
March 44 60.08333333 -16.0833 4.305247
April 60 60.08333333 -0.08333 0.000116
May 78 60.08333333 17.91667 5.342695
June 73 60.08333333 12.91667 2.776815
July 97 60.08333333 36.91667 22.6825
August 85 60.08333333 24.91667 10.33299
September 63 60.08333333 2.916667 0.141586
October 67 60.08333333 6.916667 0.796232
November 43 60.08333333 -17.0833 4.857258
December 41 60.08333333 -19.0833 6.061142
total 721 721 -2.8E-14 78.37309

(b) =sum(O-E)2/E=7.81417with k-1=4-1=3 df

critical chi-square(0.05,3)=7.8147 is more tthan calucted chi-square, so we accept null hypothesis and conclude that each months are equal

Month Oberved(O) Expected(E) (O-E) (O-E)2/E
April 60 59.75 0.25 0.001046
June 73 59.75 13.25 2.938285
September 63 59.75 3.25 0.176778
November 43 59.75 -16.75 4.695607
total 239 239 0 7.811715

(c)chi-square=52.89 with k-1=7-1=6 df

critical chi-square(0.05,6)=12.59 is less than calucted chi-square, so we reject null hypothesis and conclude that all months is not equal

Month Oberved(O) Expected(E) (O-E) (O-E)2/E
January 37 64.14285714 -27.1429 11.48584
March 44 64.14285714 -20.1429 6.325485
May 78 64.14285714 13.85714 2.993637
July 97 64.14285714 32.85714 16.83105
August 85 64.14285714 20.85714 6.782055
October 67 64.14285714 2.857143 0.127267
December 41 64.14285714 -23.1429 8.349984
total 449 52.89532

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