Using TI 89 to apply central limit theorem

Click For Summary
SUMMARY

The discussion focuses on utilizing the TI-89 calculator to apply the Central Limit Theorem for determining the distribution of the sample mean. The formula provided, P((X1 - μ) / σ/√n) < Z < (X2 - μ) / σ/√n) = P(a < Z < b) = phi(b) - phi(a), is central to this application. Users express difficulty in identifying the correct bounds for the Normal cumulative distribution function (cdf) on the TI-89, indicating a need for clarity on how to input these values effectively.

PREREQUISITES
  • Understanding of the Central Limit Theorem
  • Familiarity with the TI-89 calculator functions
  • Knowledge of Normal distribution and its properties
  • Basic calculus for evaluating integrals
NEXT STEPS
  • Research how to use the TI-89 Normal cdf function with specific bounds
  • Study the application of the Central Limit Theorem in statistical analysis
  • Learn about numerical integration techniques for approximating integrals
  • Explore statistical software alternatives for calculating sample means
USEFUL FOR

Statisticians, students in statistics courses, and anyone using the TI-89 for statistical calculations will benefit from this discussion.

jaejoon89
Messages
187
Reaction score
0
(to find distribution of sample mean)

Given

P((X1 - μ) / σ/√n) < Z < (X2 - μ) / σ/√n)) = P(a < Z < b) = phi(b) - phi(a)

where phi(z) = 1/sqrt(2*pi) * integral of exp(-z^2 / 2) dz from negative infinity to z

---

I'm sure there's some statistical way of doing this with a TI 89, but how? The Normal cdf asks me for bounds, which I don't see what they would be here. so I figure that is not the correct function on the calculator. Using the calculator would be helpful since it's obviously not easy to solve this integral analytically.
 
Physics news on Phys.org
http://www.tc3.edu/instruct/sbrown/ti83/normcalc.htm
 

Similar threads

  • · Replies 1 ·
Replies
1
Views
1K
Replies
3
Views
2K
  • · Replies 5 ·
Replies
5
Views
2K
  • · Replies 8 ·
Replies
8
Views
2K
  • · Replies 2 ·
Replies
2
Views
2K
Replies
6
Views
2K
  • · Replies 5 ·
Replies
5
Views
5K
  • · Replies 6 ·
Replies
6
Views
3K
  • · Replies 10 ·
Replies
10
Views
2K
  • · Replies 1 ·
Replies
1
Views
2K