In the early 1970s, a young man challenged an Oklahoma state law that prohibited the sale of 3.2% beer to males under age 21 but allowed its sale to females in the same age group. The case (Craig v. Boren, 429 U.S. 190, 1976) was ultimately heard by the U.S. Supreme Court. The state of Oklahoma argued that the law improved traffic safety. One of the three main pieces of data presented to the court was the result of a “random roadside survey.” This survey gathered information on gender and whether or not the driver had been drinking alcohol in the previous 2 hours. A total of 619 drivers under 21 years of age were included in the survey.
The spreadsheet of the data looked like this:Roadside survey dataDriverGenderAlcohol in lasttwo hours?Driver 1MYesDriver 2FNoDriver 3FYes………Driver 619MNo We will not use the raw data. Instead we will use the summarized data shown in the table below.Roadside survey summaryDrank alcohol in last 2 hours?YesNoTotals Male77404481 Female16122138 Totals93526619Use StatCrunch to find expected counts, the Chi-square test statistic and the P-value. (directions) Copy and paste your StatCrunch table into your post. (I WILL ATTACH BELOW)
Contingency table results:
Rows: Gender
Columns: None
Cell format
Count
(Expected count)
Male
Alcohol No Alcohol Yes Total
404
77 481
(379.89) (101.11)
Female
185
122
(146.11)
63
(38.89)
Total
526
140
666
Chi-Square test:
Statistic DF
Value
P-value
Chi-square
1 26.207558
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