# Distribution

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I need some serious explanation. I cannot even understand what to study for the frist 6 questions on the test about the formula I posted in this subject line.

The book I am using is Elementary Statistics by mario F. Triola. 8th edition.

Here is what I am to study:

Students will have 2 hours to answer 20 exam questions.

The examination covers textbook pages 226 through 472 (224

through 503), or Chapters 5, 6, 7 and 8.

First 6 questions are on the distribution, P(z <, = or > Z)

or Ch 5-1 through Ch5-6.

If you can explain how I should study for this, and what formula I should use and how to use it with the TI-83 calculator.

If you understand this, I will see if you can help me with the remaining of the study questions that follow:

Next 10 questions cover

* confidence level interval estimates (Ch 6) of the

population mean

* testing hypotheses (one-tailed and two-tailed tests) ch 7

for large samples > 30 (test statistic of z) and small

samples <30 (test statistic of t distribution)

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##### Solution Summary

The book I am using is Elementary Statistics by mario F. Triola. 8th edition.

Here is what I am to study:

Students will have 2 hours to answer 20 exam questions.

The examination covers textbook pages 226 through 472 (224

through 503), or Chapters 5, 6, 7 and 8.

First 6 questions are on the distribution, P(z <, = or > Z)

or Ch 5-1 through Ch5-6.

If you can explain how I should study for this, and what formula I should use and how to use it with the TI-83 calculator.

If you understand this, I will see if you can help me with the remaining of the study questions that follow:

Next 10 questions cover

* confidence level interval estimates (Ch 6) of the

population mean

* testing hypotheses (one-tailed and two-tailed tests) ch 7

for large samples > 30 (test statistic of z) and small

samples <30 (test statistic of t distribution)

##### Solution Preview

I think these questions should be relative to standard normal distribution. So I give you some detailed explanation and examples, which might help you understanding the chapter.

The standard normal distribution is a normal distribution with a mean of 0 and a standard deviation of 1. Normal distributions can be transformed to standard normal distributions by the formula:

where X is a score from the original normal distribution, μ is the mean of the original normal distribution, and σ is the standard deviation of original normal distribution. The standard normal distribution is sometimes called the z distribution. A z score always reflects ...

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