A study is conducted to determine the relationship between a driver’s age and the number of accidents he or she has over a 1-year period. The data are shown here.
Drivers Age x - 16, 24, 18, 17, 23, 27, 32
No. of accidents y - 3, 2, 5, 2, 0, 1, 1
a. Draw the scatter plot.
b. Compute the value of the correlation coefficient.
c. Test the significance of the correlation coefficient at alpha = 0.01.
d. Determine the regression line equation.
e. Predict the number of accidents of a driver who is 28.
a.
b.
correlation coefficient:
"r=\\frac{\\sum(x_i-\\overline{x})(y_i-\\overline{y})}{\\sqrt{\\sum(x_i-\\overline{x})^2(y_i-\\overline{y})^2}}"
"\\overline{x}=22.4,\\overline{y}=2"
"r=-0.61"
c.
Null Hypothesis: H0: r=0
Alternate Hypothesis: Ha: r≠0
test statistic:
"t=\\frac{r\\sqrt{n-2}}{\\sqrt{1-r^2}}=\\frac{-0.61\\sqrt{5}}{\\sqrt{1-0.61^2}}=-1.721"
"df=n-2=5"
critical value:
"t_{crit}=4.032"
Since "|t|<t_{crit}" we accept Null Hypothesis. Correlation coefficient IS NOT significantly different from zero. There IS NOT a significant linear relationship(correlation) between x and y.
d.
equation of regression line:
"y=ax+b"
"a=\\frac{\\sum xy-\\sum x\\sum y}{n\\sum x^2-(\\sum x)^2}=-0.1701"
"b=\\frac{\\sum y\\sum x^2-\\sum x\\sum xy}{n\\sum x^2-(\\sum x)^2}=5.816"
"y=5.816-0.1701x"
e.
number of accidents of a driver who is 28:
"y(28)=5.816-0.1701\\cdot28=1.05\\approx 1" accident
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