In: Statistics and Probability
Dorothy Kelly sells life insurance for the Prudence Insurance Company. She sells insurance by making visits to her clients homes. Dorothy believes that the number of sales should depend, to some degree, on the number of visits made. For the past several years, she kept careful records of the number of visits (x) she made each week and the number of people (y) who bought insurance that week. For a random sample of 15 such weeks, the x and y values follow.
x | 11 | 21 | 18 | 15 | 28 | 5 | 20 | 14 | 22 | 7 | 15 | 29 | 8 | 25 | 16 |
y | 1 | 10 | 9 | 4 | 8 | 2 | 5 | 6 | 8 | 3 | 5 | 10 | 6 | 10 | 7 |
In this setting we have Σx = 254, Σy = 94, Σx2 = 5060, Σy2 = 710, and Σxy = 1833.
(a) Find x, y, b, and the equation of the least-squares line. (Round your answers for x and y to two decimal places. Round your least-squares estimates to four decimal places.)
x | = | |
y | = | |
b | = | |
ŷ | = | + x |
(b) Draw a scatter diagram displaying the data. Graph the
least-squares line on your scatter diagram. Be sure to plot the
point (x, y).
(c) Find the sample correlation coefficient r and the
coefficient of determination. (Round your answers to three decimal
places.)
r = | |
r2 = |
What percentage of variation in y is explained by the
least-squares model? (Round your answer to one decimal
place.)
%
(d) Test the claim that the population correlation coefficient
ρ is positive at the 1% level of significance. (Round your
test statistic to three decimal places.)
t =
Find or estimate the P-value of the test statistic.
P-value > 0.2500.125 < P-value < 0.250 0.100 < P-value < 0.1250.075 < P-value < 0.1000.050 < P-value < 0.0750.025 < P-value < 0.0500.010 < P-value < 0.0250.005 < P-value < 0.0100.0005 < P-value < 0.005P-value < 0.0005
Conclusion
Reject the null hypothesis. There is sufficient evidence that ρ > 0.Reject the null hypothesis. There is insufficient evidence that ρ > 0. Fail to reject the null hypothesis. There is sufficient evidence that ρ > 0.Fail to reject the null hypothesis. There is insufficient evidence that ρ > 0.
(e) In a week during which Dorothy makes 21 visits, how many people
do you predict will buy insurance from her? (Round your answer to
one decimal place.)
people
(f) Find Se. (Round your answer to three
decimal places.)
Se =
(g) Find a 95% confidence interval for the number of sales Dorothy
would make in a week during which she made 21 visits. (Round your
answers to one decimal place.)
lower limit | sales |
upper limit | sales |
(h) Test the claim that the slope β of the population
least-squares line is positive at the 1% level of significance.
(Round your test statistic to three decimal places.)
t =
Find or estimate the P-value of the test statistic.
P-value > 0.2500.125 < P-value < 0.250 0.100 < P-value < 0.1250.075 < P-value < 0.1000.050 < P-value < 0.0750.025 < P-value < 0.0500.010 < P-value < 0.0250.005 < P-value < 0.0100.0005 < P-value < 0.005P-value < 0.0005
Conclusion
Reject the null hypothesis. There is sufficient evidence that β > 0.Reject the null hypothesis. There is insufficient evidence that β > 0. Fail to reject the null hypothesis. There is sufficient evidence that β > 0.Fail to reject the null hypothesis. There is insufficient evidence that β > 0.
(i) Find an 80% confidence interval for β and interpret
its meaning. (Round your answers to three decimal places.)
lower limit | |
upper limit |
Interpretation
For each less visit made, sales increase by an amount that falls within the confidence interval.For each additional visit made, sales increase by an amount that falls within the confidence interval. For each additional visit made, sales increase by an amount that falls outside the confidence interval.For each less visit made, sales increase by an amount that falls outside the confidence interval.
n= | 15.0000 | |
X̅=ΣX/n | 16.9333 | |
Y̅=ΣY/n | 6.2667 | |
sx=(√(Σx2-(Σx)2/n)/(n-1))= | 7.3627 | |
sy=(√(Σy2-(Σy)2/n)/(n-1))= | 2.9391 | |
Cov=sxy=(ΣXY-(ΣXΣY)/n)/(n-1)= | 17.2333 | |
r=Cov/(Sx*Sy)= | 0.796 | |
slope= β̂1 =r*Sy/Sx= | 0.3179 | |
intercept= β̂0 ='y̅-β1x̅= | 0.8835 |
a)
X̅=ΣX/n = | 16.93 |
Y̅=ΣY/n = | 6.27 |
b=0.3179
Least square line equation: ŷ =0.8835+0.3179*x |
b)
c)
r=0.796
r2 =0.634
63.4 %
d_)
t=r*(√(n-2)/(1-r2))= | 4.748 |
P-value < 0.0005
Reject the null hypothesis. There is sufficient evidence that ρ > 0
e)
predicted val=0.884+21*0.318= | 7.6 |
f)
Se =√(SSE/(n-2))= | 1.845 |
g)
standard error of PI=s*√(1+1/n+(x0-x̅)2/Sxx)= | 1.9245 | |
for 95 % CI value of t = | 2.160 | |
margin of error E=t*std error = | 4.158 | |
lower confidence bound=xo-E = | 3.4 | |
Upper confidence bound=xo+E= | 11.7 |
h)
t=r*(√(n-2)/(1-r2))= | 4.748 |
P-value < 0.0005
Reject the null hypothesis. There is sufficient evidence that ρ > 0
i)
std error of slope =se(β1) =s/√Sxx= | 0.0670 | |
for 90 % CI value of t = | 1.771 | |
margin of error E=t*std error = | 0.119 | |
lower confidence bound=xo-E = | 0.199 | |
Upper confidence bound=xo+E= | 0.436 |
.For each additional visit made, sales increase by an amount that falls within the confidence interval.