Respuesta :
Answer:
[0.841;6.879]
Step-by-step explanation:
Hello!
You have two independent samples:
Sample 1
X₁: tree species in an unlogged plot.
n₁= 12 plots
Unlogged 22 18 22 20 15 21 13 13 19 13 19 15
Sample 2
X₂: tree species in a plot logged 8 years earlier
n₂= 9
Logged 17 4 18 14 18 15 15 10 12
The objective of this experiment is to estimate the difference between the means of the number of species on the unlogged plots and the logged plots. Symbolically: μ₁-μ₂
To be able to estimate the difference between the two population means, I'll assume that both variables have a normal distribution and use a pooled t-statistic for the Confidence interval. (I did a quick F-test for variance homogeneity, population variances are unknown but equal)
The formula is:
(X₁[bar]-X₂[bar])±[tex]t_{(n1+n2-2);1-\alpha /2}[/tex]*(Sₐ√(1/n₁+1/n₂))
Where
sample mean sample 1 X₁[bar]= 17.50
sample mean sample 2 X₂[bar]= 13.64
S₁= 3.53
S₂= 4.50
[tex]t_{n1 + n2 - 2;1-\alpha/2} = t_{19;0.95} = 1.729[/tex]
Sₐ²= (n₁ - 1)S₁² + (n₂ - 1)S₂² = 11*(3.53)² + 8*(4.50)² = 15.74
n₁+n₂-2 19
Sₐ= 3.96
Now replace the values in the formula:
(X₁[bar]-X₂[bar])±[tex]t_{(n1+n2-2);1-\alpha /2}[/tex]*(Sₐ√1/n₁+1/n₂)
[(17.50-13.64) ± 1.729*(3.96*√(1/12+1/9))]
[3.86 ± 3.019]
[0.841;6.879]
With a confidence level of 90%, you'd expect that the interval [0.841;6.879] contains the difference between the means of the number of species on the unlogged plots and the logged plots.
I hope it helps!
The confidence interval of the tropical rain forest is 0.80 to 6.86
The confidence interval is calculated using:
[tex]CI = (\bar x_1 - \bar x_2) \pm t_{df} * \sigma_a * \sqrt{1/n_1 + 1/n_2}[/tex]
Where:
[tex]df = n_1 + n_2 - 2[/tex] --- the degrees of freedom.
n1 = 12 and n2 = 9
So, we have:
[tex]df = 12 + 9 - 2[/tex]
[tex]df = 19[/tex]
Also, we have:
[tex]\bar x_1 = \frac{22+ 18+ 22 +20 +15 +21 +13 +13 +19+ 13+ 19 +15}{12} = 17.5[/tex]
[tex]\bar x_2 = \frac{17 +4 +18+ 14 +18 +15 +15+ 10+ 12}{9} = 13.67[/tex]
Using a calculator, we have:
[tex]\sigma_1 = 3.53[/tex]
[tex]\sigma_2 = 4.50[/tex]
So, we have:
[tex]CI = (\bar x_1 - \bar x_2) \pm t_{df} * \sigma_a * \sqrt{1/n_1 + 1/n_2}[/tex]
[tex]CI = (17.5 - 13.67) \pm t_{19} * \sigma_a * \sqrt{1/12 + 1/9}[/tex]
[tex]CI = 3.83 \pm t_{19} * \sigma_a * 0.441[/tex]
Next, we have:
[tex]\sigma_a =\sqrt{\frac{(n_1 - 1)* \sigma_1^2 +(n_2- 1)* \sigma_2^2} {df}}[/tex]
So, we have:
[tex]\sigma_a =\sqrt{\frac{(12 - 1)* 3.53^2 +(9- 1)* 4.50^2} {19}}[/tex]
[tex]\sigma_a =\sqrt{\frac{299.0699}{19}}[/tex]
[tex]\sigma_a =3.97[/tex]
So, we have:
[tex]CI = 3.83 \pm t_{19} * 3.97* 0.441[/tex]
[tex]CI = 3.83 \pm t_{19} * 1.751[/tex]
At 90% confidence interval, and a degree of freedom of 19, the t value is:
[tex]t = 1.729[/tex]
So, we have:
[tex]CI = 3.83 \pm 1.729 * 1.751[/tex]
[tex]CI = 3.83 \pm 3.03[/tex]
Split
[tex]CI = (3.83 - 3.03,3.83 + 3.03)[/tex]
[tex]CI = (0.80,6.86)[/tex]
Hence, the confidence interval is 0.80 to 6.86
Read more about confidence intervals at:
https://brainly.com/question/17097944