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A Driver’s Ed program is curious if the time of year has an impact on number of car accidents in the U.S. They assumethat weather may have a significant impact on the ability of drivers to control their vehicles. They take a randomsample of 150 car accidents and record the season each occurred in. They found that 27 occurred in the Spring, 39 inthe Summer, 31 in the Fall, and 53 in the Winter.

Required:
Can it be concluded at the 0.05 level of significance that caraccidents are not equally distributed throughout the year?


Sagot :

Answer:

p-value = 0.0145

Hence, Since p-value ( 0.0145 ) is less than significance level ( 0.05 )

we reject null hypothesis.

Therefore, there is sufficient evidence to conclude that Car accidents are NOT equally distributed throughout the year

Step-by-step explanation:

Given the data in the question;

Hypothesis;

Null hypothesis             : H₀ : Car accidents are equally distributed throughout the year

Alternative hypothesis : Hₐ : Car accidents are NOT equally distributed throughout the year

significance level ∝ = 0.05

x ;

Spring = 27

Summer = 39

Fall = 31

Winter = 53

Test Statistics;

Chi Square = ∑[ (O – E)²/E ]

                         O               E                   (O – E)²/E

Spring               27            37.4                2.94

Summer            39            37.4                0.06

Fall                    31             37.4                1.1267

Winter               53            37.4                6.4067

Total                 150           150                 10.5334

so; z = ∑[ (O – E)²/E ] = 10.5334

{from table}

p-value = 0.0145

Hence, Since p-value ( 0.0145 ) is less than significance level ( 0.05 )

we reject null hypothesis.

Therefore, there is sufficient evidence to conclude that Car accidents are NOT equally distributed throughout the year

In this exercise we have to use probability knowledge to calculate the distribution during the year, so we find that:

There is sufficient evidence to conclude that car accidents are not equally distributed throughout the year.

Given the data in the question;

  • [tex]Null \ hypothesis: H_0[/tex]
  • [tex]Alternative \ hypothesis : H_a[/tex]  
  • [tex]Significance\ level = 0.05[/tex]

Now the values ​​given in the statement can be exemplified below as:

  • [tex]Spring = 27[/tex]
  • [tex]Summer = 39[/tex]
  • [tex]Fall = 31[/tex]
  • [tex]Winter = 53[/tex]

In this way, we can assemble a table of values ​​with the statistical data previously informed and using the formula given below:

[tex]Z=\sum[\frac{(O-E)^2}{E}][/tex]

[tex]Z = 10.5334[/tex]

So:

[tex]\ \ \ \ \ \ \ \ \ \ \ O \ \ \ \ \ E \ \ \ \ (O - E)^2/E\\Spring \ \ 27 \ \ 37.4 \ \ \ \ 2.94\\Summer \ 39 \ 37.4 \ \ \ \ 0.06\\Fall \ \ \ \ \ \ 31 \ 37.4 \ \ \ \ 1.1267\\Winter \ \ \ 53 \ 37.4 \ \ \ 6.4067\\Total \ 150 150 \ 10.5334[/tex]

Hence, Since pvalue ( 0.0145 ) is less than significance level ( 0.05 ), so we reject null hypothesis.

See more about probability at brainly.com/question/795909