Listed below are annual data for various years. The data are weights (metric tons) of imported lemons and car crash fatality rates per 100,000 population. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value using alphaequals0.05. Is there sufficient evidence to conclude that there is a linear correlation between lemon imports and crash fatality rates? Do the results suggest that imported lemons cause car fatalities?

Yes

No

Step-by-step explanation:

The data is as follows;

X       YX*Y         X*X         Y*Y

230      15.9365752900252.81

265      15.74160.570225246.49

358      15.45513.2128164237.16

480      15.37344230400234.09

530      14.97897280900222.01

∑X = 1863∑Y = 77.2∑X² =762589   ∑Y² = 28571.7  ∑XY = 1192.56

The correlation coefficient is gives as follows;

Where n = 5, plugging in the values, we have r= -0.95896

We now find the test statistic s follows

plugging in the values gives t = -5.858

With df = 3, we have the probability given as p = 0.00496 which is lesser than α = 0.05 we therefore reject the null hypothesis therefore, yes there is correlation between lemon imports and crash fatalities.

No, because lemon imports and car fatalities only correlate, the cause of car fatalities will be found at the point the crash occurs.  

(- 1, 0 )

step-by-step explanation:

an x- intercept is where the function crosses the x- axis.

to find the x- intercept/s look for the value of x when f(x) = 0

from the given table there are 3 values of x where f(x) = 0

when x = - 1, x = 2, x = 3

the one that is listed is (- 1, 0 )

step-by-step explanation:

is their an equation anywhere i can take a   look at it and see if i am right.